Datasets:
fix: audio iteration
Browse files
speech-emotion-recognition-dataset.py
CHANGED
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@@ -61,7 +61,7 @@ class SpeechEmotionRecognitionDataset(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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audio = dl_manager.download_and_extract(f"{_DATA}audio.zip")
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annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
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-
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN,
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gen_kwargs={
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@@ -72,33 +72,33 @@ class SpeechEmotionRecognitionDataset(datasets.GeneratorBasedBuilder):
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def _generate_examples(self, audio, annotations):
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annotations_df = pd.read_csv(annotations, sep=';')
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audio =
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for idx,
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for audio_file in sub_dir.iterdir():
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if audio_file.name.startswith('euphoric'):
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euphoric = audio_file
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elif
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joyfully = audio_file
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elif
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sad = audio_file
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elif
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surprised = audio_file
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yield idx, {
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'set_id':
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set_id,
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'euphoric':
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-
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'joyfully':
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-
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'sad':
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-
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'surprised':
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-
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'text':
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annotations_df.loc[annotations_df['set_id'] == set_id]
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['text'].values[0],
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def _split_generators(self, dl_manager):
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audio = dl_manager.download_and_extract(f"{_DATA}audio.zip")
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annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
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audio = dl_manager.iter_files(audio)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN,
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gen_kwargs={
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def _generate_examples(self, audio, annotations):
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annotations_df = pd.read_csv(annotations, sep=';')
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audio = list(audio)
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audio = [audio[i:i + 4] for i in range(0, len(audio), 4)]
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for idx, set in enumerate(audio):
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for audio_file in set:
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if 'euphoric' in audio_file:
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euphoric = audio_file
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elif 'joyfully' in audio_file:
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joyfully = audio_file
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elif 'sad' in audio_file:
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sad = audio_file
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elif 'surprised' in audio_file:
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surprised = audio_file
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set_id = Path(set[0]).parent.name
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+
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yield idx, {
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'set_id':
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set_id,
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'euphoric':
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euphoric,
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'joyfully':
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joyfully,
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'sad':
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sad,
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'surprised':
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surprised,
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'text':
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annotations_df.loc[annotations_df['set_id'] == set_id]
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['text'].values[0],
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