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38 lines
1.5 KiB
Python
38 lines
1.5 KiB
Python
# This script gets speech rate per audio recording from a voice dataset (ljspeech file and directory structure)
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# Writte by Thorsten Müller (deep-learning-german@gmx.net) and provided without any warranty.
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# https://github.com/thorstenMueller/deep-learning-german-tts/
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# https://twitter.com/ThorstenVoice
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# Changelog:
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# v0.1 - 26.09.2021 - Initial version
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import os
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import librosa
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import csv
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dataset_dir = "/Users/thorsten/Downloads/thorsten-export-20210909/" # Directory where metadata.csv is in
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out_csv_file = os.path.join(dataset_dir,"speech_rate_report.csv")
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decimal_use_comma = True # False: Splitting decimal value with a dot (.); True: Comma (,)
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out_csv = open(out_csv_file,"w")
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out_csv.write("filename;audiolength_sec;number_chars;chars_per_sec;remove_from_dataset\n")
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# Open metadata.csv file
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with open(os.path.join(dataset_dir,"metadata.csv")) as csvfile:
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reader = csv.reader(csvfile, delimiter='|')
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for row in reader:
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wav_file = os.path.join(dataset_dir,"wavs",row[0] + ".wav")
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# Gather values for report.csv output
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phrase_len = len(row[1]) - 1 # Do not count punctuation marks.
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duration = round(librosa.get_duration(filename=wav_file),2)
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char_per_sec = round(phrase_len / duration,2)
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if decimal_use_comma:
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duration = str(duration).replace(".",",")
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char_per_sec = str(char_per_sec).replace(".",",")
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out_csv.write(row[0] + ".wav;" + str(duration) + ";" + str(phrase_len) + ";" + str(char_per_sec) + ";no\n")
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out_csv.close()
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