Datasets:
Tasks:
Audio Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
< 1K
Tags:
SER
Speech Emotion Recognition
Speech Emotion Classification
Audio Classification
Audio
Emotion
License:
Upload 2 files
Browse files- parquet2csv_wav.py +38 -0
- sqe_messai_nowav.csv +0 -0
parquet2csv_wav.py
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# REQUIREMENTS
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# $ pip install scipy
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# $ pip install "polars[all]"
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# You may need to install snappy in order to run this script:
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# $ sudo pacman -S snappy
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# $ pip install python-snappy
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import polars as pl
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import numpy as np
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from scipy.io.wavfile import write
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import os
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n_cores = str(os.cpu_count())
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os.environ['OMP_NUM_THREADS'] = n_cores
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os.environ['MKL_NUM_THREADS'] = n_cores
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if not os.path.isdir('wavs'):
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os.makedirs('wavs')
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columns = ['ytid', 'ytid_seg', 'start', 'end', 'sentiment', 'happiness', 'sadness', 'anger', 'fear', 'disgust', 'surprise']
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df = pl.read_parquet('sqe_messai.parquet', columns = columns)
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df.write_csv('sqe_messai_nowav.csv')
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print(df)
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columns2 = ['ytid_seg', 'wav2numpy']
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df2 = pl.read_parquet('sqe_messai.parquet', use_pyarrow=False, columns = columns2)
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def numpy2wav(row):
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segment = os.path.splitext(os.path.basename(os.path.normpath(row[0])))[0]
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print('PROCESSED:', segment)
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write('wavs/' + segment + '.wav', 16000, np.array(row[1]))
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return segment
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df2.apply(lambda x: numpy2wav(x))
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sqe_messai_nowav.csv
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