{ "cells": [ { "cell_type": "markdown", "id": "215a158f-aa0b-49ef-aa0d-5b48344be606", "metadata": {}, "source": [ "# Track - Audio Analysis Features " ] }, { "cell_type": "code", "execution_count": 117, "id": "243bb250-65ef-4c6d-ac2c-62b689f209bd", "metadata": {}, "outputs": [], "source": [ "from glob import glob\n", "from matplotlib import pylab as plt\n", "import numpy as np\n", "import pandas as pd\n", "import json\n", "import os" ] }, { "cell_type": "code", "execution_count": 118, "id": "1e248b1d-2ce7-405e-bde1-71453a2575db", "metadata": {}, "outputs": [], "source": [ "# !pip install matplotlib" ] }, { "cell_type": "code", "execution_count": 119, "id": "9ef81303-155d-4837-b409-13505314a64a", "metadata": {}, "outputs": [], "source": [ "lst_files = glob('/Users/aadam/Downloads/acousticbrainz-lowlevel-json-20220623/lowlevel/*/*/*.json', recursive=True)" ] }, { "cell_type": "code", "execution_count": 120, "id": "812abbfd-eb97-4e01-b616-5b9bafe28daa", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'/Users/aadam/Downloads/acousticbrainz-lowlevel-json-20220623/lowlevel/61/9/619f63d9-9303-431b-b413-1681b49ae1f7-0.json'" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lst_files[0]" ] }, { "cell_type": "code", "execution_count": 248, "id": "85707697-a018-48e7-8d95-e423eed04c8e", "metadata": {}, "outputs": [], "source": [ "def read_file(file_path:str):\n", " \"\"\"\n", " Reads and returns filepath\n", " params:\n", " - file_path:str - filepath\n", " \n", " returns:\n", " dictionary data\n", " \"\"\"\n", " with open(file_path, 'r') as json_file:\n", " data = json.load(json_file)\n", " return data" ] }, { "cell_type": "markdown", "id": "5ea34718-1a2c-4ef8-96e2-6c417778343a", "metadata": {}, "source": [ "# Track Features" ] }, { "cell_type": "code", "execution_count": 249, "id": "a513e98b-891e-489d-97d8-e9f62f535a08", "metadata": {}, "outputs": [], "source": [ "data = read_file(file_path=lst_files[4])" ] }, { "cell_type": "code", "execution_count": 250, "id": "ac87e214-6264-4e96-a42d-6bac42de665d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['tonal', 'rhythm', 'lowlevel', 'metadata'])" ] }, "execution_count": 250, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.keys()" ] }, { "cell_type": "code", "execution_count": 251, "id": "d4cd7c81-613e-40d7-9947-b20008f23858", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'tags': {'asin': ['B000CS4L1E'],\n", " 'date': ['2006'],\n", " 'isrc': ['USEP40605104'],\n", " 'album': ['Fox Confessor Brings the Flood'],\n", " 'genre': ['Alternative'],\n", " 'label': ['ANTI-'],\n", " 'media': ['CD'],\n", " 'title': [\"A Widow's Toast\"],\n", " 'artist': ['Neko Case'],\n", " 'script': ['Latn'],\n", " 'barcode': ['045778677726'],\n", " 'encodedby': ['Exact Audio Copy (Secure mode)'],\n", " 'file_name': \"04 - A Widow's Toast.mp3\",\n", " 'artistsort': ['Case, Neko'],\n", " 'discnumber': ['1/1'],\n", " 'acoustid_id': ['6fd9cc72-e905-4a62-bd6c-45dbf47de44d'],\n", " 'albumartist': ['Neko Case'],\n", " 'tracknumber': ['4/12'],\n", " 'originaldate': ['2006'],\n", " 'catalognumber': ['86777-2'],\n", " 'albumartistsort': ['Case, Neko'],\n", " 'musicbrainz_albumid': ['24f52930-c7b3-4f5f-8d88-a086fc16bfcb'],\n", " 'musicbrainz_artistid': ['e13d2935-8c42-4c0a-96d7-654062acf106'],\n", " 'musicbrainz album type': ['album'],\n", " 'musicbrainz_recordingid': ['61978cc9-fcd1-4493-8ac7-a523d7853a52'],\n", " 'musicbrainz album status': ['official'],\n", " 'musicbrainz_albumartistid': ['e13d2935-8c42-4c0a-96d7-654062acf106'],\n", " 'musicbrainz_releasegroupid': ['7813c6a9-36fd-3541-8099-f877a6c72766'],\n", " 'musicbrainz album release country': ['US']},\n", " 'version': {'essentia': '2.1-beta1',\n", " 'extractor': 'music 1.0',\n", " 'essentia_git_sha': 'v2.1_beta1-28-g21ef5f4-dirty',\n", " 'essentia_build_sha': 'ca57ba49d9b1854bd80e60cf9ccf267278fb7d6b'},\n", " 'audio_properties': {'codec': 'mp3',\n", " 'length': 96.6541290283,\n", " 'downmix': 'mix',\n", " 'bit_rate': 185126,\n", " 'lossless': False,\n", " 'md5_encoded': '0477b56183d7a7c85d09d30d770e3f9c',\n", " 'replay_gain': -8.16059684753,\n", " 'sample_rate': 44100,\n", " 'equal_loudness': 0,\n", " 'analysis_sample_rate': 44100}}" ] }, "execution_count": 251, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['metadata']" ] }, { "cell_type": "code", "execution_count": 256, "id": "9271e2c6-28ec-4a8f-9da5-c7a617779d94", "metadata": {}, "outputs": [], "source": [ "def get_meta_features( track_features,\n", " meta_features=[]):\n", " \"\"\"\n", " Extracts meta features\n", "\n", " Params:\n", " - meat_features (list, optional): list of meta features to extract.\n", " Defaults to [].\n", " \"\"\"\n", " track_meta = track_features['metadata']\n", "\n", " def _flatten_nested_values(val):\n", " if isinstance(val, list):\n", " return val[0]\n", " else:\n", " return val\n", "\n", " tags = {k: _flatten_nested_values(v) for k, v in track_meta.items()}\n", " audio_properties = {k: v for k, v in track_meta.items()}\n", "\n", " return {**tags, **audio_properties}" ] }, { "cell_type": "code", "execution_count": 257, "id": "dad7f651-2560-4f8b-a76e-53a17d1e7fe8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'tags': {'asin': ['B000CS4L1E'],\n", " 'date': ['2006'],\n", " 'isrc': ['USEP40605104'],\n", " 'album': ['Fox Confessor Brings the Flood'],\n", " 'genre': ['Alternative'],\n", " 'label': ['ANTI-'],\n", " 'media': ['CD'],\n", " 'title': [\"A Widow's Toast\"],\n", " 'artist': ['Neko Case'],\n", " 'script': ['Latn'],\n", " 'barcode': ['045778677726'],\n", " 'encodedby': ['Exact Audio Copy (Secure mode)'],\n", " 'file_name': \"04 - A Widow's Toast.mp3\",\n", " 'artistsort': ['Case, Neko'],\n", " 'discnumber': ['1/1'],\n", " 'acoustid_id': ['6fd9cc72-e905-4a62-bd6c-45dbf47de44d'],\n", " 'albumartist': ['Neko Case'],\n", " 'tracknumber': ['4/12'],\n", " 'originaldate': ['2006'],\n", " 'catalognumber': ['86777-2'],\n", " 'albumartistsort': ['Case, Neko'],\n", " 'musicbrainz_albumid': ['24f52930-c7b3-4f5f-8d88-a086fc16bfcb'],\n", " 'musicbrainz_artistid': ['e13d2935-8c42-4c0a-96d7-654062acf106'],\n", " 'musicbrainz album type': ['album'],\n", " 'musicbrainz_recordingid': ['61978cc9-fcd1-4493-8ac7-a523d7853a52'],\n", " 'musicbrainz album status': ['official'],\n", " 'musicbrainz_albumartistid': ['e13d2935-8c42-4c0a-96d7-654062acf106'],\n", " 'musicbrainz_releasegroupid': ['7813c6a9-36fd-3541-8099-f877a6c72766'],\n", " 'musicbrainz album release country': ['US']},\n", " 'version': {'essentia': '2.1-beta1',\n", " 'extractor': 'music 1.0',\n", " 'essentia_git_sha': 'v2.1_beta1-28-g21ef5f4-dirty',\n", " 'essentia_build_sha': 'ca57ba49d9b1854bd80e60cf9ccf267278fb7d6b'},\n", " 'audio_properties': {'codec': 'mp3',\n", " 'length': 96.6541290283,\n", " 'downmix': 'mix',\n", " 'bit_rate': 185126,\n", " 'lossless': False,\n", " 'md5_encoded': '0477b56183d7a7c85d09d30d770e3f9c',\n", " 'replay_gain': -8.16059684753,\n", " 'sample_rate': 44100,\n", " 'equal_loudness': 0,\n", " 'analysis_sample_rate': 44100}}" ] }, "execution_count": 257, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_meta_features(data)" ] }, { "cell_type": "code", "execution_count": 252, "id": "3743e2b3-4679-4e23-9dc3-5883c718d145", "metadata": {}, "outputs": [], "source": [ "data_df = pd.DataFrame.from_dict(data['metadata'])" ] }, { "cell_type": "code", "execution_count": 253, "id": "4a030ff4-5673-4f8f-8ff1-adaf2a74852d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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tagsversionaudio_properties
asin[B000CS4L1E]NaNNaN
date[2006]NaNNaN
isrc[USEP40605104]NaNNaN
album[Fox Confessor Brings the Flood]NaNNaN
genre[Alternative]NaNNaN
label[ANTI-]NaNNaN
media[CD]NaNNaN
title[A Widow's Toast]NaNNaN
artist[Neko Case]NaNNaN
script[Latn]NaNNaN
barcode[045778677726]NaNNaN
encodedby[Exact Audio Copy (Secure mode)]NaNNaN
file_name04 - A Widow's Toast.mp3NaNNaN
artistsort[Case, Neko]NaNNaN
discnumber[1/1]NaNNaN
acoustid_id[6fd9cc72-e905-4a62-bd6c-45dbf47de44d]NaNNaN
albumartist[Neko Case]NaNNaN
tracknumber[4/12]NaNNaN
originaldate[2006]NaNNaN
catalognumber[86777-2]NaNNaN
albumartistsort[Case, Neko]NaNNaN
musicbrainz_albumid[24f52930-c7b3-4f5f-8d88-a086fc16bfcb]NaNNaN
musicbrainz_artistid[e13d2935-8c42-4c0a-96d7-654062acf106]NaNNaN
musicbrainz album type[album]NaNNaN
musicbrainz_recordingid[61978cc9-fcd1-4493-8ac7-a523d7853a52]NaNNaN
musicbrainz album status[official]NaNNaN
musicbrainz_albumartistid[e13d2935-8c42-4c0a-96d7-654062acf106]NaNNaN
musicbrainz_releasegroupid[7813c6a9-36fd-3541-8099-f877a6c72766]NaNNaN
musicbrainz album release country[US]NaNNaN
essentiaNaN2.1-beta1NaN
extractorNaNmusic 1.0NaN
essentia_git_shaNaNv2.1_beta1-28-g21ef5f4-dirtyNaN
essentia_build_shaNaNca57ba49d9b1854bd80e60cf9ccf267278fb7d6bNaN
codecNaNNaNmp3
lengthNaNNaN96.654129
downmixNaNNaNmix
bit_rateNaNNaN185126
losslessNaNNaNFalse
md5_encodedNaNNaN0477b56183d7a7c85d09d30d770e3f9c
replay_gainNaNNaN-8.160597
sample_rateNaNNaN44100
equal_loudnessNaNNaN0
analysis_sample_rateNaNNaN44100
\n", "
" ], "text/plain": [ " tags \\\n", "asin [B000CS4L1E] \n", "date [2006] \n", "isrc [USEP40605104] \n", "album [Fox Confessor Brings the Flood] \n", "genre [Alternative] \n", "label [ANTI-] \n", "media [CD] \n", "title [A Widow's Toast] \n", "artist [Neko Case] \n", "script [Latn] \n", "barcode [045778677726] \n", "encodedby [Exact Audio Copy (Secure mode)] \n", "file_name 04 - A Widow's Toast.mp3 \n", "artistsort [Case, Neko] \n", "discnumber [1/1] \n", "acoustid_id [6fd9cc72-e905-4a62-bd6c-45dbf47de44d] \n", "albumartist [Neko Case] \n", "tracknumber [4/12] \n", "originaldate [2006] \n", "catalognumber [86777-2] \n", "albumartistsort [Case, Neko] \n", "musicbrainz_albumid [24f52930-c7b3-4f5f-8d88-a086fc16bfcb] \n", "musicbrainz_artistid [e13d2935-8c42-4c0a-96d7-654062acf106] \n", "musicbrainz album type [album] \n", "musicbrainz_recordingid [61978cc9-fcd1-4493-8ac7-a523d7853a52] \n", "musicbrainz album status [official] \n", "musicbrainz_albumartistid [e13d2935-8c42-4c0a-96d7-654062acf106] \n", "musicbrainz_releasegroupid [7813c6a9-36fd-3541-8099-f877a6c72766] \n", "musicbrainz album release country [US] \n", "essentia NaN \n", "extractor NaN \n", "essentia_git_sha NaN \n", "essentia_build_sha NaN \n", "codec NaN \n", "length NaN \n", "downmix NaN \n", "bit_rate NaN \n", "lossless NaN \n", "md5_encoded NaN \n", "replay_gain NaN \n", "sample_rate NaN \n", "equal_loudness NaN \n", "analysis_sample_rate NaN \n", "\n", " version \\\n", "asin NaN \n", "date NaN \n", "isrc NaN \n", "album NaN \n", "genre NaN \n", "label NaN \n", "media NaN \n", "title NaN \n", "artist NaN \n", "script NaN \n", "barcode NaN \n", "encodedby NaN \n", "file_name NaN \n", "artistsort NaN \n", "discnumber NaN \n", "acoustid_id NaN \n", "albumartist NaN \n", "tracknumber NaN \n", "originaldate NaN \n", "catalognumber NaN \n", "albumartistsort NaN \n", "musicbrainz_albumid NaN \n", "musicbrainz_artistid NaN \n", "musicbrainz album type NaN \n", "musicbrainz_recordingid NaN \n", "musicbrainz album status NaN \n", "musicbrainz_albumartistid NaN \n", "musicbrainz_releasegroupid NaN \n", "musicbrainz album release country NaN \n", "essentia 2.1-beta1 \n", "extractor music 1.0 \n", "essentia_git_sha v2.1_beta1-28-g21ef5f4-dirty \n", "essentia_build_sha ca57ba49d9b1854bd80e60cf9ccf267278fb7d6b \n", "codec NaN \n", "length NaN \n", "downmix NaN \n", "bit_rate NaN \n", "lossless NaN \n", "md5_encoded NaN \n", "replay_gain NaN \n", "sample_rate NaN \n", "equal_loudness NaN \n", "analysis_sample_rate NaN \n", "\n", " audio_properties \n", "asin NaN \n", "date NaN \n", "isrc NaN \n", "album NaN \n", "genre NaN \n", "label NaN \n", "media NaN \n", "title NaN \n", "artist NaN \n", "script NaN \n", "barcode NaN \n", "encodedby NaN \n", "file_name NaN \n", "artistsort NaN \n", "discnumber NaN \n", "acoustid_id NaN \n", "albumartist NaN \n", "tracknumber NaN \n", "originaldate NaN \n", "catalognumber NaN \n", "albumartistsort NaN \n", "musicbrainz_albumid NaN \n", "musicbrainz_artistid NaN \n", "musicbrainz album type NaN \n", "musicbrainz_recordingid NaN \n", "musicbrainz album status NaN \n", "musicbrainz_albumartistid NaN \n", "musicbrainz_releasegroupid NaN \n", "musicbrainz album release country NaN \n", "essentia NaN \n", "extractor NaN \n", "essentia_git_sha NaN \n", "essentia_build_sha NaN \n", "codec mp3 \n", "length 96.654129 \n", "downmix mix \n", "bit_rate 185126 \n", "lossless False \n", "md5_encoded 0477b56183d7a7c85d09d30d770e3f9c \n", "replay_gain -8.160597 \n", "sample_rate 44100 \n", "equal_loudness 0 \n", "analysis_sample_rate 44100 " ] }, "execution_count": 253, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_df" ] }, { "cell_type": "code", "execution_count": 258, "id": "0bcbd675-578f-4ca0-baa9-edeee6f973b1", "metadata": {}, "outputs": [], "source": [ "def get_track_metadata(track_features):\n", " \"\"\"returns track metadata \"\"\"\n", " \n", " def _flatten_value(val):\n", " if isinstance(val, list):\n", " return val[0]\n", " else:\n", " return val\n", " \n", " tags = {k:_flatten_value(v) for k,v in track_features['metadata']['tags'].items()}\n", " audio_properties = {k:v for k,v in track_features['metadata']['audio_properties'].items()}\n", " \n", " return {**tags, **audio_properties}" ] }, { "cell_type": "markdown", "id": "20e4a927-9065-47ab-b15d-3a0daa4e586e", "metadata": {}, "source": [ "# Metadata Features" ] }, { "cell_type": "code", "execution_count": 259, "id": "393bd6a3-d07a-4d4e-b41f-f61df57c3335", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'asin': 'B000CS4L1E',\n", " 'date': '2006',\n", " 'isrc': 'USEP40605104',\n", " 'album': 'Fox Confessor Brings the Flood',\n", " 'genre': 'Alternative',\n", " 'label': 'ANTI-',\n", " 'media': 'CD',\n", " 'title': \"A Widow's Toast\",\n", " 'artist': 'Neko Case',\n", " 'script': 'Latn',\n", " 'barcode': '045778677726',\n", " 'encodedby': 'Exact Audio Copy (Secure mode)',\n", " 'file_name': \"04 - A Widow's Toast.mp3\",\n", " 'artistsort': 'Case, Neko',\n", " 'discnumber': '1/1',\n", " 'acoustid_id': '6fd9cc72-e905-4a62-bd6c-45dbf47de44d',\n", " 'albumartist': 'Neko Case',\n", " 'tracknumber': '4/12',\n", " 'originaldate': '2006',\n", " 'catalognumber': '86777-2',\n", " 'albumartistsort': 'Case, Neko',\n", " 'musicbrainz_albumid': '24f52930-c7b3-4f5f-8d88-a086fc16bfcb',\n", " 'musicbrainz_artistid': 'e13d2935-8c42-4c0a-96d7-654062acf106',\n", " 'musicbrainz album type': 'album',\n", " 'musicbrainz_recordingid': '61978cc9-fcd1-4493-8ac7-a523d7853a52',\n", " 'musicbrainz album status': 'official',\n", " 'musicbrainz_albumartistid': 'e13d2935-8c42-4c0a-96d7-654062acf106',\n", " 'musicbrainz_releasegroupid': '7813c6a9-36fd-3541-8099-f877a6c72766',\n", " 'musicbrainz album release country': 'US',\n", " 'codec': 'mp3',\n", " 'length': 96.6541290283,\n", " 'downmix': 'mix',\n", " 'bit_rate': 185126,\n", " 'lossless': False,\n", " 'md5_encoded': '0477b56183d7a7c85d09d30d770e3f9c',\n", " 'replay_gain': -8.16059684753,\n", " 'sample_rate': 44100,\n", " 'equal_loudness': 0,\n", " 'analysis_sample_rate': 44100}" ] }, "execution_count": 259, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_track_metadata(data)" ] }, { "cell_type": "markdown", "id": "1abe0b57-2b5b-4f89-8b1e-4ef9ec92f46e", "metadata": {}, "source": [ "#### Observations\n", "- some of the features that can be used from here include:\n", " > * Artist Name\n", " > * Album Name\n", " > * Track Title\n", " > * Script\n", " > * Length\n", " > * Label " ] }, { "cell_type": "markdown", "id": "d323d517-916b-4073-abc5-81ec737c6cf9", "metadata": {}, "source": [ "## Low Level Features\n", "\n", "Low Level Features of Interest\n", "- hfc - high freq. content of spectogram\n", "- mfcc - mel-frequency cepstrum (MFC) applies Fourier transforms and maps it to a mel scale. It allows for signals to be decomposed and enhanced to be cleaner signals.\n", "- gfcc - gammatone-frequency cepstral coefficients (GFCC features)\n", "\n", "- melbands - frequentyly used as features for speaker verification tasks.\n", "- erbbands - frequenctly used as features for excitation patterns from audio.\n", "- barkbands - algorithm computes energy in Bark bands of a spectrum\n", "- dissonance - measures perceptual roughness of the sound and is based on the roughness of its spectral peaks\n", "- average_loudness - average kloudness\n", "- zerocrossingrate\n", "- silence_rate_60dB (rate of silence at various decibles)\n", "- silence_rate_20dB (silence rate at various decibles)\n", "- silence_rate_30dB (silence rate are various decibles)\n", "- pitch_salience - computes prominence of pitch\n", "\n", "See - https://essentia.upf.edu/algorithms_overview.html\n" ] }, { "cell_type": "code", "execution_count": 187, "id": "48385a9f-23ce-47ac-8d10-5eb085f474e4", "metadata": {}, "outputs": [], "source": [ "low_level_feat_df = pd.DataFrame.from_dict(data['lowlevel'])" ] }, { "cell_type": "code", "execution_count": 269, "id": "06df6dea-c482-4c3d-b215-102e3e3aa5da", "metadata": {}, "outputs": [], "source": [ "LOW_LEVEL_FEATURES = [\n", " 'hfc', 'gfcc', 'mfcc', 'erbbands', 'melbands', 'barkbands',\n", " 'dissonance', 'average_loudness', 'zerocrossingrate',\n", " 'silence_rate_60dB', 'silence_rate_20dB', 'silence_rate_30dB',\n", " 'pitch_salience'\n", "]\n", "\n", "\n", "def get_lowlevel_features( track_features,\n", " lowlevel_features=LOW_LEVEL_FEATURES):\n", " \"\"\"\n", "\n", "\n", " Args:\n", " track_features (_type_): _description_\n", " lowlevel_features (list, optional): _description_. \n", " Defaults to [].\n", " \"\"\"\n", "\n", " lowlevel_feat = track_features['lowlevel']\n", "\n", " features = {}\n", "\n", " for feat_i in lowlevel_features:\n", " # copy features\n", " if feat_i in lowlevel_feat.keys():\n", " print(feat_i)\n", " if isinstance(lowlevel_feat[feat_i], dict):\n", " features[f'{feat_i}_mean'] = lowlevel_feat[feat_i]['mean']\n", " else:\n", " features[f'{feat_i}'] = lowlevel_feat[feat_i]\n", "\n", " return features" ] }, { "cell_type": "code", "execution_count": 270, "id": "cd3c06cd-785e-432e-9987-5fb845fea99d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "hfc\n", "gfcc\n", "mfcc\n", "erbbands\n", "melbands\n", "barkbands\n", "dissonance\n", "average_loudness\n", "zerocrossingrate\n", "silence_rate_60dB\n", "silence_rate_20dB\n", "silence_rate_30dB\n", "pitch_salience\n" ] }, { "data": { "text/plain": [ "{'hfc_mean': 211.905654907,\n", " 'gfcc_mean': [-100.561828613,\n", " 93.7877731323,\n", " -58.0473632812,\n", " -1.16108334064,\n", " -12.0799598694,\n", " -23.171628952,\n", " -6.37576436996,\n", " -21.6759319305,\n", " -6.72486686707,\n", " -13.5865297318,\n", " -18.9070644379,\n", " -10.8763027191,\n", " -1.93911898136],\n", " 'mfcc_mean': [-762.092224121,\n", " 159.955947876,\n", " 8.34285449982,\n", " 36.7348403931,\n", " 3.77959752083,\n", " 14.4094352722,\n", " -1.88195514679,\n", " -1.44467115402,\n", " 9.43763542175,\n", " 2.69493508339,\n", " -12.9817895889,\n", " -7.92509841919,\n", " 1.8965228796],\n", " 'erbbands_mean': [0.0388528816402,\n", " 0.514706790447,\n", " 3.30664968491,\n", " 9.3819770813,\n", " 19.0323085785,\n", " 11.2836694717,\n", " 8.93479728699,\n", " 15.8766393661,\n", " 15.8648481369,\n", " 22.9912471771,\n", " 22.7852115631,\n", " 20.4359130859,\n", " 20.2262687683,\n", " 38.6229171753,\n", " 12.710855484,\n", " 8.78093242645,\n", " 7.47412967682,\n", " 11.4077577591,\n", " 18.6090545654,\n", " 36.6046638489,\n", " 40.655582428,\n", " 9.60532188416,\n", " 4.52329587936,\n", " 4.66354322433,\n", " 5.74083471298,\n", " 6.64155864716,\n", " 6.83242607117,\n", " 5.46853733063,\n", " 2.88219475746,\n", " 1.11075079441,\n", " 0.334792822599,\n", " 0.110629633069,\n", " 0.0373452194035,\n", " 0.0206526145339,\n", " 0.0142482975498,\n", " 0.0130489952862,\n", " 0.0539267770946,\n", " 0.13758212328,\n", " 0.0835763514042,\n", " 0.0197872389108],\n", " 'melbands_mean': [0.000442433985882,\n", " 0.00138166965917,\n", " 0.00196563941427,\n", " 0.00119279313367,\n", " 0.000306964793708,\n", " 0.000347872555722,\n", " 0.000243215952651,\n", " 0.000257801235421,\n", " 0.000177657566383,\n", " 0.00012565421639,\n", " 0.000101929952507,\n", " 0.000163914475706,\n", " 4.47857673862e-05,\n", " 3.00648862321e-05,\n", " 1.83009124157e-05,\n", " 1.3954336282e-05,\n", " 2.19715984713e-05,\n", " 2.80932508758e-05,\n", " 3.65756641258e-05,\n", " 5.63996072742e-05,\n", " 4.36170339526e-05,\n", " 1.00445959106e-05,\n", " 3.94395510739e-06,\n", " 3.88331272916e-06,\n", " 3.74550245397e-06,\n", " 3.49625133822e-06,\n", " 4.91977971251e-06,\n", " 4.28170642408e-06,\n", " 4.46123203801e-06,\n", " 3.69404165212e-06,\n", " 3.00141982734e-06,\n", " 1.77845799954e-06,\n", " 9.77059926299e-07,\n", " 4.56408770333e-07,\n", " 2.0088158692e-07,\n", " 1.00310877826e-07,\n", " 5.33021875526e-08,\n", " 2.67972986023e-08,\n", " 1.82391701742e-08,\n", " 1.6760600019e-08],\n", " 'barkbands_mean': [0.000180528266355,\n", " 0.00186749803834,\n", " 0.00347364274785,\n", " 0.00398211181164,\n", " 0.00459971139207,\n", " 0.00172328110784,\n", " 0.00114529707935,\n", " 0.00112000363879,\n", " 0.000923252431676,\n", " 0.00103559787385,\n", " 0.000356570497388,\n", " 0.000241241956246,\n", " 0.000155781614012,\n", " 0.000250045617577,\n", " 0.000475762819406,\n", " 0.000823611568194,\n", " 0.000162435229868,\n", " 8.00170237198e-05,\n", " 9.54841598286e-05,\n", " 0.000149280182086,\n", " 0.000155820147484,\n", " 7.12461260264e-05,\n", " 1.42257722473e-05,\n", " 3.25459950545e-06,\n", " 1.89679008145e-06,\n", " 2.65319085884e-05,\n", " 0.000794759136625],\n", " 'dissonance_mean': 0.451761752367,\n", " 'average_loudness': 0.639868736267,\n", " 'zerocrossingrate_mean': 0.399466842413,\n", " 'silence_rate_60dB_mean': 0.138568684459,\n", " 'silence_rate_20dB_mean': 1,\n", " 'silence_rate_30dB_mean': 0.97670507431,\n", " 'pitch_salience_mean': 0.536871552467}" ] }, "execution_count": 270, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_lowlevel_features(data)" ] }, { "cell_type": "code", "execution_count": 188, "id": "ccd6f19b-b025-43b4-b21f-00fc98236874", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['hfc', 'gfcc', 'mfcc', 'erbbands', 'melbands', 'barkbands',\n", " 'dissonance', 'spectral_rms', 'spectral_flux', 'erbbands_crest',\n", " 'melbands_crest', 'pitch_salience', 'barkbands_crest',\n", " 'erbbands_spread', 'melbands_spread', 'spectral_energy',\n", " 'spectral_spread', 'average_loudness', 'barkbands_spread',\n", " 'spectral_entropy', 'spectral_rolloff', 'zerocrossingrate',\n", " 'erbbands_kurtosis', 'erbbands_skewness', 'melbands_kurtosis',\n", " 'melbands_skewness', 'silence_rate_20dB', 'silence_rate_30dB',\n", " 'silence_rate_60dB', 'spectral_centroid', 'spectral_decrease',\n", " 'spectral_kurtosis', 'spectral_skewness', 'barkbands_kurtosis',\n", " 'barkbands_skewness', 'dynamic_complexity', 'spectral_complexity',\n", " 'spectral_strongpeak', 'erbbands_flatness_db', 'melbands_flatness_db',\n", " 'barkbands_flatness_db', 'spectral_energyband_low',\n", " 'spectral_contrast_coeffs', 'spectral_energyband_high',\n", " 'spectral_contrast_valleys', 'spectral_energyband_middle_low',\n", " 'spectral_energyband_middle_high'],\n", " dtype='object')" ] }, "execution_count": 188, "metadata": {}, "output_type": "execute_result" } ], "source": [ "low_level_feat_df.columns" ] }, { "cell_type": "code", "execution_count": 207, "id": "8c8e0d5b-ce47-4a11-80c2-c6c53fd8baba", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "max 1.000000\n", "min 0.000000\n", "var 0.119363\n", "dvar 0.015603\n", "mean 0.138569\n", "dmean 0.015854\n", "dvar2 0.036477\n", "dmean2 0.031716\n", "median 0.000000\n", "cov NaN\n", "icov NaN\n", "Name: silence_rate_60dB, dtype: float64" ] }, "execution_count": 207, "metadata": {}, "output_type": "execute_result" } ], "source": [ "low_level_feat_df['silence_rate_60dB']" ] }, { "cell_type": "code", "execution_count": 210, "id": "9e136c85-766f-45a1-af7c-2571315e7ce9", "metadata": {}, "outputs": [], "source": [ "LOW_LEVEL_FEATURES = [\n", " 'hfc', 'gfcc', 'mfcc', 'erbbands', 'melbands', 'barkbands',\n", " 'dissonance', 'average_loudness', 'zerocrossingrate',\n", " 'silence_rate_60dB', 'silence_rate_20dB', 'silence_rate_30dB',\n", " 'pitch_salience'\n", "]\n", "def get_lowlevel_features(track_features=low_level_feat_df, lowlevel_features=LOW_LEVEL_FEATURES):\n", " \"\"\"\n", "\n", "\n", " Args:\n", " track_features (_type_): _description_\n", " lowlevel_features (list, optional): _description_. \n", " Defaults to [].\n", " \"\"\"\n", "\n", " lowlevel_feat = track_features\n", "\n", " features = {}\n", "\n", " for feat_i in lowlevel_features:\n", "\n", " # assign features\n", " if feat_i in lowlevel_feat.keys():\n", " features[f'{feat_i}_mean'] = lowlevel_feat[feat_i]['mean']\n", "\n", " return features" ] }, { "cell_type": "code", "execution_count": 211, "id": "80de17ac-ab63-4b06-9472-1c031618372f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'hfc_mean': 211.905654907,\n", " 'gfcc_mean': [-100.561828613,\n", " 93.7877731323,\n", " -58.0473632812,\n", " -1.16108334064,\n", " -12.0799598694,\n", " -23.171628952,\n", " -6.37576436996,\n", " -21.6759319305,\n", " -6.72486686707,\n", " -13.5865297318,\n", " -18.9070644379,\n", " -10.8763027191,\n", " -1.93911898136],\n", " 'mfcc_mean': [-762.092224121,\n", " 159.955947876,\n", " 8.34285449982,\n", " 36.7348403931,\n", " 3.77959752083,\n", " 14.4094352722,\n", " -1.88195514679,\n", " -1.44467115402,\n", " 9.43763542175,\n", " 2.69493508339,\n", " -12.9817895889,\n", " -7.92509841919,\n", " 1.8965228796],\n", " 'erbbands_mean': [0.0388528816402,\n", " 0.514706790447,\n", " 3.30664968491,\n", " 9.3819770813,\n", " 19.0323085785,\n", " 11.2836694717,\n", " 8.93479728699,\n", " 15.8766393661,\n", " 15.8648481369,\n", " 22.9912471771,\n", " 22.7852115631,\n", " 20.4359130859,\n", " 20.2262687683,\n", " 38.6229171753,\n", " 12.710855484,\n", " 8.78093242645,\n", " 7.47412967682,\n", " 11.4077577591,\n", " 18.6090545654,\n", " 36.6046638489,\n", " 40.655582428,\n", " 9.60532188416,\n", " 4.52329587936,\n", " 4.66354322433,\n", " 5.74083471298,\n", " 6.64155864716,\n", " 6.83242607117,\n", " 5.46853733063,\n", " 2.88219475746,\n", " 1.11075079441,\n", " 0.334792822599,\n", " 0.110629633069,\n", " 0.0373452194035,\n", " 0.0206526145339,\n", " 0.0142482975498,\n", " 0.0130489952862,\n", " 0.0539267770946,\n", " 0.13758212328,\n", " 0.0835763514042,\n", " 0.0197872389108],\n", " 'melbands_mean': [0.000442433985882,\n", " 0.00138166965917,\n", " 0.00196563941427,\n", " 0.00119279313367,\n", " 0.000306964793708,\n", " 0.000347872555722,\n", " 0.000243215952651,\n", " 0.000257801235421,\n", " 0.000177657566383,\n", " 0.00012565421639,\n", " 0.000101929952507,\n", " 0.000163914475706,\n", " 4.47857673862e-05,\n", " 3.00648862321e-05,\n", " 1.83009124157e-05,\n", " 1.3954336282e-05,\n", " 2.19715984713e-05,\n", " 2.80932508758e-05,\n", " 3.65756641258e-05,\n", " 5.63996072742e-05,\n", " 4.36170339526e-05,\n", " 1.00445959106e-05,\n", " 3.94395510739e-06,\n", " 3.88331272916e-06,\n", " 3.74550245397e-06,\n", " 3.49625133822e-06,\n", " 4.91977971251e-06,\n", " 4.28170642408e-06,\n", " 4.46123203801e-06,\n", " 3.69404165212e-06,\n", " 3.00141982734e-06,\n", " 1.77845799954e-06,\n", " 9.77059926299e-07,\n", " 4.56408770333e-07,\n", " 2.0088158692e-07,\n", " 1.00310877826e-07,\n", " 5.33021875526e-08,\n", " 2.67972986023e-08,\n", " 1.82391701742e-08,\n", " 1.6760600019e-08],\n", " 'barkbands_mean': [0.000180528266355,\n", " 0.00186749803834,\n", " 0.00347364274785,\n", " 0.00398211181164,\n", " 0.00459971139207,\n", " 0.00172328110784,\n", " 0.00114529707935,\n", " 0.00112000363879,\n", " 0.000923252431676,\n", " 0.00103559787385,\n", " 0.000356570497388,\n", " 0.000241241956246,\n", " 0.000155781614012,\n", " 0.000250045617577,\n", " 0.000475762819406,\n", " 0.000823611568194,\n", " 0.000162435229868,\n", " 8.00170237198e-05,\n", " 9.54841598286e-05,\n", " 0.000149280182086,\n", " 0.000155820147484,\n", " 7.12461260264e-05,\n", " 1.42257722473e-05,\n", " 3.25459950545e-06,\n", " 1.89679008145e-06,\n", " 2.65319085884e-05,\n", " 0.000794759136625],\n", " 'dissonance_mean': 0.451761752367,\n", " 'average_loudness_mean': 0.639868736267,\n", " 'zerocrossingrate_mean': 0.399466842413,\n", " 'silence_rate_60dB_mean': 0.138568684459,\n", " 'silence_rate_20dB_mean': 1.0,\n", " 'silence_rate_30dB_mean': 0.97670507431,\n", " 'pitch_salience_mean': 0.536871552467}" ] }, "execution_count": 211, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_lowlevel_features()" ] }, { "cell_type": "code", "execution_count": 189, "id": "144d960c-6b19-4732-98bd-32ce974faaf1", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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hfcgfccmfccerbbandsmelbandsbarkbandsdissonancespectral_rmsspectral_fluxerbbands_crest...spectral_strongpeakerbbands_flatness_dbmelbands_flatness_dbbarkbands_flatness_dbspectral_energyband_lowspectral_contrast_coeffsspectral_energyband_highspectral_contrast_valleysspectral_energyband_middle_lowspectral_energyband_middle_high
max2.230382e+03NaNNaN[0.820002496243, 14.249256134, 82.9038925171, ...[0.010191350244, 0.0349953696132, 0.0289594046...[0.00319805461913, 0.0488674640656, 0.08788613...0.4999141.618911e-023.609046e-0130.548428...247.9144900.3985330.6624610.4922241.147767e-01[-0.222845345736, -0.444878041744, -0.53200232...3.909439e-02[-5.51698303223, -4.72332572937, -5.4998517036...1.718472e-017.942636e-02
min1.077043e-16NaNNaN[1.63639084747e-22, 9.8976613254e-22, 3.147829...[1.3594755524e-24, 1.71048000104e-24, 1.617334...[5.07885266164e-25, 5.02665718681e-24, 1.13785...0.2329623.121226e-126.461675e-112.733708...0.0000000.0494740.0034660.0458911.005459e-23[-0.98065340519, -0.987037360668, -0.975755393...7.081175e-21[-27.9198455811, -27.9055843353, -27.846807479...1.555582e-221.220252e-21
var3.563898e+04NaNNaN[0.00360228447244, 0.984209656715, 44.52894973...[5.37078847174e-07, 7.09855930836e-06, 8.61569...[6.63043522309e-08, 1.16369874377e-05, 4.41847...0.0011667.100399e-062.417618e-0321.641146...474.4247740.0021260.0098710.0050681.149918e-04[0.0117595661432, 0.00685589713976, 0.00726224...9.154720e-06[7.75352907181, 8.7395362854, 8.24626255035, 8...2.968303e-043.724462e-05
dvar1.058214e+04NaNNaN[0.00196999870241, 0.591968536377, 22.10923767...[3.0394062378e-07, 3.51018547917e-06, 3.047154...[5.31074810795e-08, 7.41760686651e-06, 2.25610...0.0005266.011729e-074.047796e-047.933722...493.9215090.0005150.0010450.0007164.570858e-05[0.00182882277295, 0.00168276682962, 0.0009994...2.967666e-06[0.118304029107, 0.141670420766, 0.15115506947...8.860978e-059.667431e-06
mean2.119057e+02[-100.561828613, 93.7877731323, -58.0473632812...[-762.092224121, 159.955947876, 8.34285449982,...[0.0388528816402, 0.514706790447, 3.3066496849...[0.000442433985882, 0.00138166965917, 0.001965...[0.000180528266355, 0.00186749803834, 0.003473...0.4517624.948100e-038.317015e-0211.119345...10.2533850.1646390.3090190.1930887.301841e-03[-0.618553638458, -0.766318440437, -0.79607868...9.625010e-04[-7.86846446991, -7.61468935013, -8.3579969406...1.363592e-023.669869e-03
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5 rows × 47 columns

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" ], "text/plain": [ " hfc gfcc \\\n", "max 2.230382e+03 NaN \n", "min 1.077043e-16 NaN \n", "var 3.563898e+04 NaN \n", "dvar 1.058214e+04 NaN \n", "mean 2.119057e+02 [-100.561828613, 93.7877731323, -58.0473632812... \n", "\n", " mfcc \\\n", "max NaN \n", "min NaN \n", "var NaN \n", "dvar NaN \n", "mean [-762.092224121, 159.955947876, 8.34285449982,... \n", "\n", " erbbands \\\n", "max [0.820002496243, 14.249256134, 82.9038925171, ... \n", "min [1.63639084747e-22, 9.8976613254e-22, 3.147829... \n", "var [0.00360228447244, 0.984209656715, 44.52894973... \n", "dvar [0.00196999870241, 0.591968536377, 22.10923767... \n", "mean [0.0388528816402, 0.514706790447, 3.3066496849... \n", "\n", " melbands \\\n", "max [0.010191350244, 0.0349953696132, 0.0289594046... \n", "min [1.3594755524e-24, 1.71048000104e-24, 1.617334... \n", "var [5.37078847174e-07, 7.09855930836e-06, 8.61569... \n", "dvar [3.0394062378e-07, 3.51018547917e-06, 3.047154... \n", "mean [0.000442433985882, 0.00138166965917, 0.001965... \n", "\n", " barkbands dissonance \\\n", "max [0.00319805461913, 0.0488674640656, 0.08788613... 0.499914 \n", "min [5.07885266164e-25, 5.02665718681e-24, 1.13785... 0.232962 \n", "var [6.63043522309e-08, 1.16369874377e-05, 4.41847... 0.001166 \n", "dvar [5.31074810795e-08, 7.41760686651e-06, 2.25610... 0.000526 \n", "mean [0.000180528266355, 0.00186749803834, 0.003473... 0.451762 \n", "\n", " spectral_rms spectral_flux erbbands_crest ... spectral_strongpeak \\\n", "max 1.618911e-02 3.609046e-01 30.548428 ... 247.914490 \n", "min 3.121226e-12 6.461675e-11 2.733708 ... 0.000000 \n", "var 7.100399e-06 2.417618e-03 21.641146 ... 474.424774 \n", "dvar 6.011729e-07 4.047796e-04 7.933722 ... 493.921509 \n", "mean 4.948100e-03 8.317015e-02 11.119345 ... 10.253385 \n", "\n", " erbbands_flatness_db melbands_flatness_db barkbands_flatness_db \\\n", "max 0.398533 0.662461 0.492224 \n", "min 0.049474 0.003466 0.045891 \n", "var 0.002126 0.009871 0.005068 \n", "dvar 0.000515 0.001045 0.000716 \n", "mean 0.164639 0.309019 0.193088 \n", "\n", " spectral_energyband_low \\\n", "max 1.147767e-01 \n", "min 1.005459e-23 \n", "var 1.149918e-04 \n", "dvar 4.570858e-05 \n", "mean 7.301841e-03 \n", "\n", " spectral_contrast_coeffs \\\n", "max [-0.222845345736, -0.444878041744, -0.53200232... \n", "min [-0.98065340519, -0.987037360668, -0.975755393... \n", "var [0.0117595661432, 0.00685589713976, 0.00726224... \n", "dvar [0.00182882277295, 0.00168276682962, 0.0009994... \n", "mean [-0.618553638458, -0.766318440437, -0.79607868... \n", "\n", " spectral_energyband_high \\\n", "max 3.909439e-02 \n", "min 7.081175e-21 \n", "var 9.154720e-06 \n", "dvar 2.967666e-06 \n", "mean 9.625010e-04 \n", "\n", " spectral_contrast_valleys \\\n", "max [-5.51698303223, -4.72332572937, -5.4998517036... \n", "min [-27.9198455811, -27.9055843353, -27.846807479... \n", "var [7.75352907181, 8.7395362854, 8.24626255035, 8... \n", "dvar [0.118304029107, 0.141670420766, 0.15115506947... \n", "mean [-7.86846446991, -7.61468935013, -8.3579969406... \n", "\n", " spectral_energyband_middle_low spectral_energyband_middle_high \n", "max 1.718472e-01 7.942636e-02 \n", "min 1.555582e-22 1.220252e-21 \n", "var 2.968303e-04 3.724462e-05 \n", "dvar 8.860978e-05 9.667431e-06 \n", "mean 1.363592e-02 3.669869e-03 \n", "\n", "[5 rows x 47 columns]" ] }, "execution_count": 189, "metadata": {}, "output_type": "execute_result" } ], "source": [ "low_level_feat_df.head()" ] }, { "cell_type": "code", "execution_count": 190, "id": "e15a6539-70c0-4ff4-8a93-1c810f7c7e85", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.0323736295104" ] }, "execution_count": 190, "metadata": {}, "output_type": "execute_result" } ], "source": [ "low_level_feat_df['spectral_energy']['mean']" ] }, { "cell_type": "code", "execution_count": 204, "id": "b5478365-0214-43ba-8234-cd07160d204d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "max 2.230382e+03\n", "min 1.077043e-16\n", "var 3.563898e+04\n", 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hfcgfccmfccdissonancespectral_centroidspectral_energy
max2.230382e+03NaNNaN0.4999141.183121e+042.686395e-01
min1.077043e-16NaNNaN0.2329621.238715e+029.985604e-21
var3.563898e+04NaNNaN0.0011662.574786e+068.517976e-04
dvar1.058214e+04NaNNaN0.0005261.269049e+051.668527e-04
mean2.119057e+02[-100.561828613, 93.7877731323, -58.0473632812...[-762.092224121, 159.955947876, 8.34285449982,...0.4517629.862650e+023.237363e-02
dmean7.603786e+01NaNNaN0.0248791.946134e+029.236554e-03
dvar22.749189e+04NaNNaN0.0014032.163730e+054.016345e-04
dmean21.204306e+02NaNNaN0.0407782.800619e+021.432104e-02
median1.741270e+02NaNNaN0.4583035.435768e+022.712697e-02
covNaN[[38862.0546875, 2675.2121582, -5493.80517578,...[[18833.1347656, 2214.2512207, -3985.25292969,...NaNNaNNaN
icovNaN[[0.000116281458759, -0.000416491617216, 0.000...[[0.000199125468498, -0.000271070864983, 0.000...NaNNaNNaN
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NaN \n", "\n", " spectral_centroid spectral_energy \n", "max 1.183121e+04 2.686395e-01 \n", "min 1.238715e+02 9.985604e-21 \n", "var 2.574786e+06 8.517976e-04 \n", "dvar 1.269049e+05 1.668527e-04 \n", "mean 9.862650e+02 3.237363e-02 \n", "dmean 1.946134e+02 9.236554e-03 \n", "dvar2 2.163730e+05 4.016345e-04 \n", "dmean2 2.800619e+02 1.432104e-02 \n", "median 5.435768e+02 2.712697e-02 \n", "cov NaN NaN \n", "icov NaN NaN " ] }, "execution_count": 191, "metadata": {}, "output_type": "execute_result" } ], "source": [ "low_level_feat_df[['hfc', 'gfcc', 'mfcc', 'dissonance', 'spectral_centroid', 'spectral_energy']]" ] }, { "cell_type": "code", "execution_count": 192, "id": "e6cd39b6-9867-4be8-aece-cc4c8ba83fc1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'GFCC - mean')" ] }, "execution_count": 192, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['lowlevel']['gfcc']['mean']).reshape(1,13))\n", "plt.title('GFCC - mean')" ] }, { "cell_type": "code", "execution_count": 193, "id": "bce44e4a-6dbc-48c0-a4f8-7e031a824eb9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'GFCC - cov')" ] }, "execution_count": 193, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['lowlevel']['gfcc']['cov']).reshape(13,13))\n", "plt.title('GFCC - cov')" ] }, { "cell_type": "code", "execution_count": 194, "id": "5951baea-a1a0-451d-901b-9a78baa2e7d6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'MFCC - mean')" ] }, "execution_count": 194, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['lowlevel']['mfcc']['mean']).reshape(1,13))\n", "plt.title('MFCC - mean')" ] }, { "cell_type": "code", "execution_count": 195, "id": "57e8d20a-ccdf-4c1e-ae44-b344b8fe33be", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'MFCC - cov')" ] }, "execution_count": 195, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['lowlevel']['mfcc']['cov']).reshape(13,13))\n", "plt.title('MFCC - cov')" ] }, { "cell_type": "code", "execution_count": 196, "id": "75a74a31-80e5-4d97-ba5d-b6bf74ab249c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 196, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['lowlevel']['erbbands']['mean']).reshape(4,10))" ] }, { "cell_type": "code", "execution_count": 197, "id": "58229d33-2f2a-4ca2-9d96-002ecd906951", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 197, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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maxminvardvarmeandmeandvar2dmean2median
0100.0326250.0247340.0927520.0841290.0661240.1464830.021918
1100.0145600.0154370.0510350.0539310.0411950.0941200.010824
2100.0121660.0117630.0446690.0425700.0301420.0740160.009865
3100.0094780.0096200.0451440.0420050.0262190.0733660.012930
4100.0112780.0100890.0573900.0515080.0273870.0886480.019178
5100.0240090.0163870.0861150.0696200.0450270.1196940.029350
6100.0274840.0191560.0865290.0711750.0523800.1245220.029454
7100.0220900.0203440.0679150.0683410.0573520.1227090.017661
8100.0228810.0239870.0640850.0708930.0646640.1293400.012695
9100.0275420.0298770.0819690.0938090.0809790.1671230.018001
10100.0560200.0450440.1709660.1644780.1207630.2867960.065567
11100.1137970.0672710.3467420.2389950.1663760.4098870.216262
12100.1341420.0607060.3948220.2212040.1515520.3762380.251035
13100.0813690.0482340.2499690.1852660.1309000.3213390.117554
14100.0451890.0428140.1361030.1398900.1135780.2453530.044103
15100.0363490.0397080.0985100.1094710.1059240.1972170.022663
16100.0277190.0339180.0711250.0887380.1014370.1618660.011727
17100.0177370.0226000.0486930.0619500.0638680.1126120.007431
18100.0141810.0184310.0492630.0572800.0513600.1034850.011047
19100.0243910.0230520.0681300.0714420.0581690.1251360.015121
20100.0266880.0254310.0731410.0757960.0664300.1316320.015814
21100.0237460.0257410.0849740.0914260.0693410.1603880.024891
22100.0713820.0548850.1840570.1715260.1402630.2934060.061802
23100.0947000.0584060.2343480.1849330.1416790.3159370.084038
24100.0698290.0517050.1934190.1644620.1441300.2850140.072153
25100.0731750.0523170.1728970.1526570.1424780.2702360.044292
26100.0533630.0428530.1322780.1277570.1215450.2271920.029049
27100.0329250.0343720.0858780.0936920.0986610.1709800.013325
28100.0301450.0387090.0716300.0924480.1106330.1690800.008577
29100.0310860.0355050.0765550.0930270.1009890.1686400.011585
30100.0373090.0383930.0948960.1061510.1070660.1932840.017226
31100.0531360.0506790.1266330.1406220.1422070.2547260.023698
32100.0666670.0599020.1773190.1870140.1712510.3374690.056122
33100.0988090.0608100.2508710.1950830.1539630.3390570.098707
34100.0933900.0584890.2490930.1964760.1515660.3407670.104432
35100.0632190.0428190.1671590.1442380.1108370.2507200.053422
\n", "
" ], "text/plain": [ " max min var dvar mean dmean dvar2 dmean2 \\\n", "0 1 0 0.032625 0.024734 0.092752 0.084129 0.066124 0.146483 \n", "1 1 0 0.014560 0.015437 0.051035 0.053931 0.041195 0.094120 \n", "2 1 0 0.012166 0.011763 0.044669 0.042570 0.030142 0.074016 \n", "3 1 0 0.009478 0.009620 0.045144 0.042005 0.026219 0.073366 \n", "4 1 0 0.011278 0.010089 0.057390 0.051508 0.027387 0.088648 \n", "5 1 0 0.024009 0.016387 0.086115 0.069620 0.045027 0.119694 \n", "6 1 0 0.027484 0.019156 0.086529 0.071175 0.052380 0.124522 \n", "7 1 0 0.022090 0.020344 0.067915 0.068341 0.057352 0.122709 \n", "8 1 0 0.022881 0.023987 0.064085 0.070893 0.064664 0.129340 \n", "9 1 0 0.027542 0.029877 0.081969 0.093809 0.080979 0.167123 \n", "10 1 0 0.056020 0.045044 0.170966 0.164478 0.120763 0.286796 \n", "11 1 0 0.113797 0.067271 0.346742 0.238995 0.166376 0.409887 \n", "12 1 0 0.134142 0.060706 0.394822 0.221204 0.151552 0.376238 \n", "13 1 0 0.081369 0.048234 0.249969 0.185266 0.130900 0.321339 \n", "14 1 0 0.045189 0.042814 0.136103 0.139890 0.113578 0.245353 \n", "15 1 0 0.036349 0.039708 0.098510 0.109471 0.105924 0.197217 \n", "16 1 0 0.027719 0.033918 0.071125 0.088738 0.101437 0.161866 \n", "17 1 0 0.017737 0.022600 0.048693 0.061950 0.063868 0.112612 \n", "18 1 0 0.014181 0.018431 0.049263 0.057280 0.051360 0.103485 \n", "19 1 0 0.024391 0.023052 0.068130 0.071442 0.058169 0.125136 \n", "20 1 0 0.026688 0.025431 0.073141 0.075796 0.066430 0.131632 \n", "21 1 0 0.023746 0.025741 0.084974 0.091426 0.069341 0.160388 \n", "22 1 0 0.071382 0.054885 0.184057 0.171526 0.140263 0.293406 \n", "23 1 0 0.094700 0.058406 0.234348 0.184933 0.141679 0.315937 \n", "24 1 0 0.069829 0.051705 0.193419 0.164462 0.144130 0.285014 \n", "25 1 0 0.073175 0.052317 0.172897 0.152657 0.142478 0.270236 \n", "26 1 0 0.053363 0.042853 0.132278 0.127757 0.121545 0.227192 \n", "27 1 0 0.032925 0.034372 0.085878 0.093692 0.098661 0.170980 \n", "28 1 0 0.030145 0.038709 0.071630 0.092448 0.110633 0.169080 \n", "29 1 0 0.031086 0.035505 0.076555 0.093027 0.100989 0.168640 \n", "30 1 0 0.037309 0.038393 0.094896 0.106151 0.107066 0.193284 \n", "31 1 0 0.053136 0.050679 0.126633 0.140622 0.142207 0.254726 \n", "32 1 0 0.066667 0.059902 0.177319 0.187014 0.171251 0.337469 \n", "33 1 0 0.098809 0.060810 0.250871 0.195083 0.153963 0.339057 \n", "34 1 0 0.093390 0.058489 0.249093 0.196476 0.151566 0.340767 \n", "35 1 0 0.063219 0.042819 0.167159 0.144238 0.110837 0.250720 \n", "\n", " median \n", "0 0.021918 \n", "1 0.010824 \n", "2 0.009865 \n", "3 0.012930 \n", "4 0.019178 \n", "5 0.029350 \n", "6 0.029454 \n", "7 0.017661 \n", "8 0.012695 \n", "9 0.018001 \n", "10 0.065567 \n", "11 0.216262 \n", "12 0.251035 \n", "13 0.117554 \n", "14 0.044103 \n", "15 0.022663 \n", "16 0.011727 \n", "17 0.007431 \n", "18 0.011047 \n", "19 0.015121 \n", "20 0.015814 \n", "21 0.024891 \n", "22 0.061802 \n", "23 0.084038 \n", "24 0.072153 \n", "25 0.044292 \n", "26 0.029049 \n", "27 0.013325 \n", "28 0.008577 \n", "29 0.011585 \n", "30 0.017226 \n", "31 0.023698 \n", "32 0.056122 \n", "33 0.098707 \n", "34 0.104432 \n", "35 0.053422 " ] }, "execution_count": 199, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(data['tonal']['hpcp'])" ] }, { "cell_type": "code", "execution_count": 200, "id": "b16485b9-bcc1-4c05-bd86-94ead95ea52f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 200, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['tonal']['hpcp']['mean']).reshape(6,6))" ] }, { "cell_type": "code", "execution_count": 201, "id": "de2a5f1b-c834-4047-a7d2-6a16bd8b9002", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dict_keys(['hpcp', 'thpcp', 'key_key', 'key_scale', 'chords_key', 'chords_scale', 'hpcp_entropy', 'key_strength', 'chords_strength', 'chords_histogram', 'tuning_frequency', 'chords_number_rate', 'chords_changes_rate', 'tuning_diatonic_strength', 'tuning_equal_tempered_deviation', 'tuning_nontempered_energy_ratio'])\n" ] } ], "source": [ "# tonal features\n", "print(data['tonal'].keys())" ] }, { "cell_type": "code", "execution_count": 218, "id": "5f0930bd-6f3a-4677-83d2-d37058587649", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.00576092163101\n" ] } ], "source": [ "# tonal features\n", "print(data['tonal']['chords_number_rate'])" ] }, { "cell_type": "markdown", "id": "6b40d2e7-0fab-4a38-860a-17ad8985be8e", "metadata": {}, "source": [ "## Chord Histogram" ] }, { "cell_type": "code", "execution_count": 203, "id": "8105bd2c-312d-4b73-b039-358c87e04698", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 203, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# tonal features\n", "plt.imshow(np.array(data['tonal']['chords_histogram']).reshape(6,4))" ] }, { "cell_type": "markdown", "id": "e7ad18f6-2370-49ad-99e6-331ef8871d0b", "metadata": {}, "source": [ "### THPCP" ] }, { "cell_type": "code", "execution_count": 104, "id": "8da65464-2e69-4846-a985-8c133497bd91", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 104, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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cska68iAnnVFcI//60GAnsXPnTtHpdLJ161b5448/ZNGiReLn5ycmk0nt0FSxfPlyKSwslKqqKjlx4oQYjUYJCAiQa9euqR1aj2lsbJTS0lIpLS0VAPLpp59KaWmpXLlyRURE1q1bJ35+fnLgwAEpKyuTGTNmSEREhLS0tKgcueN0l5PGxkZ5//33pbi4WKqqquTIkSMyduxYGTZsmLS2tqodukMsWbJEfH19pbCwUGpra61Lc3OzdczixYslLCxMjh49KmfPnhWDwSAGg0HFqB3rUTmpqKiQtWvXytmzZ6WqqkoOHDggkZGRMmnSJJUjd5xVq1ZJUVGRVFVVSVlZmaxatUo0Go389NNPIuJ6NSLSfU6eZI24TBMjIrJx40YJCwsTrVYr8fHxcurUKbVDUs2cOXMkNDRUtFqtDBw4UObMmSMVFRVqh9Wjjh07JgBslpSUFBG5f5r16tWrJTg4WHQ6nSQmJkp5ebm6QTtYdzlpbm6WKVOmSGBgoHh4eEh4eLikpqY+1f8R6CwXAOS7776zjmlpaZF3331X+vfvL56enjJr1iypra1VL2gHe1ROqqurZdKkSeLv7y86nU6GDh0qK1askPr6enUDd6C3335bwsPDRavVSmBgoCQmJlobGBHXqxGR7nPyJGtEIyJi32c3REREROpziWNiiIiI6OnDJoaIiIicEpsYIiIickpsYoiIiMgpsYkhIiIip8QmhoiIiJwSmxgiIiJySmxiiIiIyCmxiSEiIiKnxCaGiIiInBKbGCIiInJKbGKIiIjIKf0fS1OskKJix/sAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['tonal']['thpcp']).reshape(1,36))" ] }, { "cell_type": "markdown", "id": "a49dfa28-aeda-41eb-bce9-a45d1883a545", "metadata": {}, "source": [ "#### Observations \n", "- interesting properties showing some patterns - since music in a way a pattern of sound. This patterns could prove to be descriminative. \n", "- patterns are even more prominent for THPCP feature - which shows an almost even spacing." ] }, { "cell_type": "markdown", "id": "2e3d0738-9008-4826-a682-7ed6ef99ae1c", "metadata": {}, "source": [ "Observations " ] }, { "cell_type": "markdown", "id": "bad91190-3cae-4a91-8760-cb289691c17e", "metadata": {}, "source": [ "### HPCP" ] }, { "cell_type": "code", "execution_count": 105, "id": "c5f18457-537e-4e7a-b5d8-0ee67a990110", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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35100.0632190.0428190.1671590.1442380.1108370.2507200.053422
\n", "
" ], "text/plain": [ " max min var dvar mean dmean dvar2 dmean2 \\\n", "0 1 0 0.032625 0.024734 0.092752 0.084129 0.066124 0.146483 \n", "1 1 0 0.014560 0.015437 0.051035 0.053931 0.041195 0.094120 \n", "2 1 0 0.012166 0.011763 0.044669 0.042570 0.030142 0.074016 \n", "3 1 0 0.009478 0.009620 0.045144 0.042005 0.026219 0.073366 \n", "4 1 0 0.011278 0.010089 0.057390 0.051508 0.027387 0.088648 \n", "5 1 0 0.024009 0.016387 0.086115 0.069620 0.045027 0.119694 \n", "6 1 0 0.027484 0.019156 0.086529 0.071175 0.052380 0.124522 \n", "7 1 0 0.022090 0.020344 0.067915 0.068341 0.057352 0.122709 \n", "8 1 0 0.022881 0.023987 0.064085 0.070893 0.064664 0.129340 \n", "9 1 0 0.027542 0.029877 0.081969 0.093809 0.080979 0.167123 \n", "10 1 0 0.056020 0.045044 0.170966 0.164478 0.120763 0.286796 \n", "11 1 0 0.113797 0.067271 0.346742 0.238995 0.166376 0.409887 \n", "12 1 0 0.134142 0.060706 0.394822 0.221204 0.151552 0.376238 \n", "13 1 0 0.081369 0.048234 0.249969 0.185266 0.130900 0.321339 \n", "14 1 0 0.045189 0.042814 0.136103 0.139890 0.113578 0.245353 \n", "15 1 0 0.036349 0.039708 0.098510 0.109471 0.105924 0.197217 \n", "16 1 0 0.027719 0.033918 0.071125 0.088738 0.101437 0.161866 \n", "17 1 0 0.017737 0.022600 0.048693 0.061950 0.063868 0.112612 \n", "18 1 0 0.014181 0.018431 0.049263 0.057280 0.051360 0.103485 \n", "19 1 0 0.024391 0.023052 0.068130 0.071442 0.058169 0.125136 \n", "20 1 0 0.026688 0.025431 0.073141 0.075796 0.066430 0.131632 \n", "21 1 0 0.023746 0.025741 0.084974 0.091426 0.069341 0.160388 \n", "22 1 0 0.071382 0.054885 0.184057 0.171526 0.140263 0.293406 \n", "23 1 0 0.094700 0.058406 0.234348 0.184933 0.141679 0.315937 \n", "24 1 0 0.069829 0.051705 0.193419 0.164462 0.144130 0.285014 \n", "25 1 0 0.073175 0.052317 0.172897 0.152657 0.142478 0.270236 \n", "26 1 0 0.053363 0.042853 0.132278 0.127757 0.121545 0.227192 \n", "27 1 0 0.032925 0.034372 0.085878 0.093692 0.098661 0.170980 \n", "28 1 0 0.030145 0.038709 0.071630 0.092448 0.110633 0.169080 \n", "29 1 0 0.031086 0.035505 0.076555 0.093027 0.100989 0.168640 \n", "30 1 0 0.037309 0.038393 0.094896 0.106151 0.107066 0.193284 \n", "31 1 0 0.053136 0.050679 0.126633 0.140622 0.142207 0.254726 \n", "32 1 0 0.066667 0.059902 0.177319 0.187014 0.171251 0.337469 \n", "33 1 0 0.098809 0.060810 0.250871 0.195083 0.153963 0.339057 \n", "34 1 0 0.093390 0.058489 0.249093 0.196476 0.151566 0.340767 \n", "35 1 0 0.063219 0.042819 0.167159 0.144238 0.110837 0.250720 \n", "\n", " median \n", "0 0.021918 \n", "1 0.010824 \n", "2 0.009865 \n", "3 0.012930 \n", "4 0.019178 \n", "5 0.029350 \n", "6 0.029454 \n", "7 0.017661 \n", "8 0.012695 \n", "9 0.018001 \n", "10 0.065567 \n", "11 0.216262 \n", "12 0.251035 \n", "13 0.117554 \n", "14 0.044103 \n", "15 0.022663 \n", "16 0.011727 \n", "17 0.007431 \n", "18 0.011047 \n", "19 0.015121 \n", "20 0.015814 \n", "21 0.024891 \n", "22 0.061802 \n", "23 0.084038 \n", "24 0.072153 \n", "25 0.044292 \n", "26 0.029049 \n", "27 0.013325 \n", "28 0.008577 \n", "29 0.011585 \n", "30 0.017226 \n", "31 0.023698 \n", "32 0.056122 \n", "33 0.098707 \n", "34 0.104432 \n", "35 0.053422 " ] }, "execution_count": 105, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(data['tonal']['hpcp'])" ] }, { "cell_type": "code", "execution_count": 106, "id": "1cc61b6e-f45a-4601-a3b1-0d16d8a791a9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 106, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(np.array(data['tonal']['hpcp']['mean']).reshape(1,36))" ] }, { "cell_type": "code", "execution_count": 107, "id": "69b6fd02-dd59-49ef-aa4c-e9e6b264b8d4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['tonal', 'rhythm', 'lowlevel', 'metadata'])" ] }, "execution_count": 107, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.keys()" ] }, { "cell_type": "code", "execution_count": 238, "id": "1e166bbe-3c3b-4638-bc7f-c182e1e6ac22", "metadata": {}, "outputs": [], "source": [ "TONAL_FEATURES = [\n", " 'hpcp', 'thpcp', 'key_key', 'key_scale', 'key_strength',\n", " 'chords_key', 'chords_strength',\n", " 'tuning_frequency', 'chords_number_rate', 'chords_changes_rate',\n", " 'tuning_diatonic_strength', 'chords_histogram'\n", "]\n", "\n", "def get_tonal_features(track_features=data,\n", " tonal_features=TONAL_FEATURES):\n", " \"\"\"\n", "\n", " Args:\n", " track_features (_type_): _description_\n", " tonal_features (_type_, optional): _description_.\n", " Defaults to TONAL_FEATURES.\n", " \"\"\"\n", " tonal_feats = track_features['tonal']\n", "\n", " features = {}\n", "\n", " for feat_i in tonal_features:\n", "\n", " # assign\n", " if feat_i in ['hpcp', 'chords_strength']:\n", " features[f'{feat_i}_mean'] = tonal_feats[feat_i]['mean']\n", " else:\n", " features[feat_i] = tonal_feats[feat_i]\n", "\n", " return features" ] }, { "cell_type": "code", "execution_count": 239, "id": "46c96f07-71e4-42de-b649-e8c2e7593abb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'hpcp_mean': [0.0927517861128,\n", " 0.0510349087417,\n", " 0.0446694158018,\n", " 0.0451443269849,\n", " 0.0573899000883,\n", " 0.0861146375537,\n", " 0.0865294933319,\n", " 0.0679150372744,\n", " 0.0640851184726,\n", " 0.0819691717625,\n", " 0.170965984464,\n", " 0.346741646528,\n", " 0.39482191205,\n", " 0.249969467521,\n", " 0.136103108525,\n", " 0.098510183394,\n", " 0.0711254626513,\n", " 0.048692908138,\n", " 0.0492634922266,\n", " 0.0681301057339,\n", " 0.073140963912,\n", " 0.084973692894,\n", " 0.184057474136,\n", " 0.234348267317,\n", " 0.193418592215,\n", " 0.17289686203,\n", " 0.132277831435,\n", " 0.0858784466982,\n", " 0.0716303661466,\n", " 0.0765554085374,\n", " 0.0948960706592,\n", " 0.126633316278,\n", " 0.177319422364,\n", " 0.250871151686,\n", " 0.249093264341,\n", " 0.167159244418],\n", " 'thpcp': [1,\n", " 0.633119523525,\n", " 0.344720244408,\n", " 0.249505355954,\n", " 0.180145680904,\n", " 0.123328790069,\n", " 0.124773956835,\n", " 0.172559082508,\n", " 0.185250520706,\n", " 0.215220302343,\n", " 0.46617847681,\n", " 0.593554377556,\n", " 0.489888191223,\n", " 0.437911003828,\n", " 0.335031628609,\n", " 0.217511862516,\n", " 0.181424498558,\n", " 0.193898588419,\n", " 0.240351587534,\n", " 0.320735275745,\n", " 0.449112415314,\n", " 0.635403335094,\n", " 0.630900323391,\n", " 0.42337885499,\n", " 0.234920561314,\n", " 0.129260584712,\n", " 0.113138139248,\n", " 0.114340983331,\n", " 0.145356416702,\n", " 0.218110069633,\n", " 0.219160825014,\n", " 0.172014355659,\n", " 0.162313982844,\n", " 0.207610487938,\n", " 0.433020502329,\n", " 0.878222882748],\n", " 'key_key': 'F',\n", " 'key_scale': 'minor',\n", " 'key_strength': 0.786747932434,\n", " 'chords_key': 'F',\n", " 'chords_strength_mean': 0.524988055229,\n", " 'tuning_frequency': 447.174194336,\n", " 'chords_number_rate': 0.00576092163101,\n", " 'chords_changes_rate': 0.0854536741972,\n", " 'tuning_diatonic_strength': 0.699474155903,\n", " 'chords_histogram': [18.2909259796,\n", " 7.20115232468,\n", " 1.63226115704,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 5.85693693161,\n", " 6.4330291748,\n", " 10.7057132721,\n", " 0,\n", " 0.144023045897,\n", " 0,\n", " 0,\n", " 7.24915981293,\n", " 5.08881425858,\n", " 10.9937591553,\n", " 0.144023045897,\n", " 0,\n", " 0,\n", " 0,\n", " 6.57705211639,\n", " 5.13682174683,\n", " 14.5463275909]}" ] }, "execution_count": 239, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_tonal_features()" ] }, { "cell_type": "markdown", "id": "2eb01278-def7-4cd4-a50a-5390a78b6b21", "metadata": {}, "source": [ "# Rhythmic Features" ] }, { "cell_type": "code", "execution_count": 108, "id": "493701d3-0480-4780-9e20-2576f72ac838", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['bpm', 'onset_rate', 'beats_count', 'danceability', 'beats_loudness', 'beats_position', 'beats_loudness_band_ratio', 'bpm_histogram_first_peak_bpm', 'bpm_histogram_second_peak_bpm', 'bpm_histogram_first_peak_spread', 'bpm_histogram_first_peak_weight', 'bpm_histogram_second_peak_spread', 'bpm_histogram_second_peak_weight'])" ] }, "execution_count": 108, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['rhythm'].keys()" ] }, { "cell_type": "code", "execution_count": 109, "id": "3658e6d9-7ac7-4233-8bef-fee79d0412d5", "metadata": {}, "outputs": [], "source": [ "rythmic_features = ['bpm', 'onset_rate', 'beats_count', 'danceability', 'beats_loudness', 'beats_position', 'beats_loudness_band_ratio']" ] }, { "cell_type": "code", "execution_count": 110, "id": "28b423b2-6946-40b0-ae10-c5d9d6dc0c1e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2.79282546043" ] }, "execution_count": 110, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['rhythm']['onset_rate']" ] }, { "cell_type": "code", "execution_count": 240, "id": "f331fbbd-5e07-4d39-9aaf-9ada3ad65341", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "139.393737793" ] }, "execution_count": 240, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['rhythm']['bpm']" ] }, { "cell_type": "code", "execution_count": 111, "id": "411f3a02-3548-4e11-8019-3f44d8afe7f1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "216" ] }, "execution_count": 111, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['rhythm']['beats_count']" ] }, { "cell_type": "code", "execution_count": 112, "id": "8319361d-56d1-4bad-b1c5-b67acee5394f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.845048427582" ] }, "execution_count": 112, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['rhythm']['danceability']" ] }, { "cell_type": "code", "execution_count": 113, "id": "aab192e7-971e-4172-8fb3-6f34894c3302", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.0347795151174" ] }, "execution_count": 113, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['rhythm']['beats_loudness']['mean']" ] }, { "cell_type": "code", "execution_count": 114, "id": "2e681b1a-0f36-4d09-b456-dee730eeddb2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.000785038690083" ] }, "execution_count": 114, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['rhythm']['beats_loudness']['var']" ] }, { "cell_type": "code", "execution_count": 115, "id": "b1fc5461-799d-420d-afb9-7f48d2daba5b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(6,)" ] }, "execution_count": 115, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.array(data['rhythm']['beats_loudness_band_ratio']['mean']).shape" ] }, { "cell_type": "code", "execution_count": 116, "id": "e9345f87-0d2b-449b-9fbf-2a97b6929f43", "metadata": {}, "outputs": [], "source": [ "# np.array(data['rhythm']['beats_position'])" ] }, { "cell_type": "code", "execution_count": 246, "id": "13269da8-9ec0-43b2-8557-0ddd0d250af6", "metadata": {}, "outputs": [], "source": [ "RYTHMIC_FEATURES = [\n", " 'bpm', 'onset_rate', 'beats_count', 'beats_loudness',\n", " 'danceability', 'beats_loudness', 'beats_position',\n", " 'beats_loudness_band_ratio'\n", "]\n", "\n", "\n", "def get_rythmic_features(track_features,\n", " rythmic_features=RYTHMIC_FEATURES):\n", " \"\"\"\n", "\n", " Params:\n", " track_features (_type_): _description_\n", " rythmic_features (_type_, optional): _description_.\n", " Defaults to RYTHMIC_FEATURES.\n", " \"\"\"\n", "\n", " tonal_feats = track_features['rhythm']\n", "\n", " features = {}\n", "\n", " for feat_i in rythmic_features:\n", "\n", " # assign\n", " if feat_i in ['beats_loudness', 'beats_loudness_band_ratio']:\n", " features[f'{feat_i}_mean'] = tonal_feats[feat_i]['mean']\n", " else:\n", " features[feat_i] = tonal_feats[feat_i]\n", "\n", " return features" ] }, { "cell_type": "code", "execution_count": 247, "id": "9e9c4052-e3af-4708-b9a2-83eaf36d445a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'bpm': 139.393737793,\n", " 'onset_rate': 2.79282546043,\n", " 'beats_count': 216,\n", " 'beats_loudness_mean': 0.0347795151174,\n", " 'danceability': 0.845048427582,\n", " 'beats_position': [0.545668900013,\n", " 1.11455774307,\n", " 1.69505667686,\n", " 2.27555561066,\n", " 2.85605430603,\n", " 3.43655323982,\n", " 4.01705217361,\n", " 4.55111122131,\n", " 5.08516979218,\n", " 5.60761880875,\n", " 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" 25.6696586609,\n", " 26.0527877808,\n", " 26.4243087769,\n", " 26.7958278656,\n", " 27.1673469543,\n", " 27.5504760742,\n", " 27.9336051941,\n", " 28.2935142517,\n", " 28.6534233093,\n", " 29.0249423981,\n", " 29.3964614868,\n", " 29.7912006378,\n", " 30.1859397888,\n", " 30.5690689087,\n", " 30.9521980286,\n", " 31.3701572418,\n", " 31.776506424,\n", " 32.1828575134,\n", " 32.5892066956,\n", " 33.0187759399,\n", " 33.4483451843,\n", " 33.8779144287,\n", " 34.3423118591,\n", " 34.8067131042,\n", " 35.2711105347,\n", " 35.7819480896,\n", " 36.2927894592,\n", " 36.8036270142,\n", " 37.3144645691,\n", " 37.8253059387,\n", " 38.3361434937,\n", " 38.8353729248,\n", " 39.3462142944,\n", " 39.8454399109,\n", " 40.4723815918,\n", " 41.0877075195,\n", " 41.703037262,\n", " 42.3183670044,\n", " 42.9336967468,\n", " 43.5490226746,\n", " 44.164352417,\n", " 44.6984100342,\n", " 45.2208595276,\n", " 45.743309021,\n", " 46.2657585144,\n", " 46.7882080078,\n", " 47.3106575012,\n", " 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70.1823120117,\n", " 70.6234893799,\n", " 71.0762786865,\n", " 71.5406799316,\n", " 72.0050811768,\n", " 72.4694747925,\n", " 72.9338760376,\n", " 73.3866653442,\n", " 73.8278427124,\n", " 74.280632019,\n", " 74.7334213257,\n", " 75.1862106323,\n", " 75.638999939,\n", " 76.0801773071,\n", " 76.5213623047,\n", " 76.9625396729,\n", " 77.4153289795,\n", " 77.8565063477,\n", " 78.2976837158,\n", " 78.738861084,\n", " 79.1916503906,\n", " 79.6328353882,\n", " 80.0740127563,\n", " 80.4571380615,\n", " 80.8402709961,\n", " 81.2233963013,\n", " 81.6181411743,\n", " 82.0012664795,\n", " 82.3960113525,\n", " 82.7675247192,\n", " 83.1506576538,\n", " 83.5221786499,\n", " 83.8820877075,\n", " 84.2536010742,\n", " 84.6251220703,\n", " 85.0314712524,\n", " 85.449432373,\n", " 85.8673934937,\n", " 86.2853469849,\n", " 86.7033081055,\n", " 87.1328811646,\n", " 87.5624465942,\n", " 87.9920196533,\n", " 88.4099731445,\n", " 88.8395462036,\n", " 89.2110671997,\n", " 89.5825805664,\n", " 89.9541015625,\n", " 90.3256225586,\n", " 90.6971435547,\n", " 91.0686569214,\n", " 91.428565979,\n", " 91.788482666,\n", " 92.1599960327,\n", " 92.5431289673,\n", " 92.9262542725,\n", " 93.309387207,\n", " 93.7389526367,\n", " 94.1801376343,\n", " 94.6213150024,\n", " 95.0624923706,\n", " 95.5036697388,\n", " 95.9448471069],\n", " 'beats_loudness_band_ratio_mean': [0.356514573097,\n", " 0.127730980515,\n", " 0.0733089148998,\n", " 0.0472876615822,\n", " 0.0516629181802,\n", " 0.357276290655]}" ] }, "execution_count": 247, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_rythmic_features(data)" ] }, { "cell_type": "code", "execution_count": null, "id": "cbe664bb-1719-48a7-ac17-4c30e234a5cf", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.6" } }, "nbformat": 4, "nbformat_minor": 5 }