beginner/audio_datasets_tutorial
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참고
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오디오 데이터셋#
``torchaudio``는 공용으로 접근할 수 있는 일반적인 데이터셋에 쉽게 접근할 수 있는 기능을 제공합니다. 사용할 수 있는 데이터셋 목록은 공식 문서를 참고하세요.
importtorch importtorchaudio print(torch.__version__) print(torchaudio.__version__)
2.8.0+cu128 2.8.0+cu128
importos importIPython importmatplotlib.pyplotasplt _SAMPLE_DIR = "_assets" YESNO_DATASET_PATH = os.path.join(_SAMPLE_DIR, "yes_no") os.makedirs(YESNO_DATASET_PATH, exist_ok=True) defplot_specgram(waveform, sample_rate, title="Spectrogram"): waveform = waveform.numpy() figure, ax = plt.subplots() ax.specgram(waveform[0], Fs=sample_rate) figure.suptitle(title) figure.tight_layout()
여기서 torchaudio.datasets.YESNO 데이터셋의 사용 방법을 볼 수 있습니다.
dataset = torchaudio.datasets.YESNO(YESNO_DATASET_PATH, download=True)
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i = 1 waveform, sample_rate, label = dataset[i] plot_specgram(waveform, sample_rate, title=f"Sample {i}: {label}") IPython.display.Audio(waveform, rate=sample_rate)
/opt/conda/lib/python3.11/site-packages/torchaudio/_backend/utils.py:213: UserWarning: In 2.9, this function's implementation will be changed to use torchaudio.load_with_torchcodec` under the hood. Some parameters like ``normalize``, ``format``, ``buffer_size``, and ``backend`` will be ignored. We recommend that you port your code to rely directly on TorchCodec's decoder instead: https://docs.pytorch.org/torchcodec/stable/generated/torchcodec.decoders.AudioDecoder.html#torchcodec.decoders.AudioDecoder. /opt/conda/lib/python3.11/site-packages/torchaudio/_backend/ffmpeg.py:88: UserWarning: torio.io._streaming_media_decoder.StreamingMediaDecoder has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see https://github.com/pytorch/audio/issues/3902 for more information. It will be removed from the 2.9 release.
i = 3 waveform, sample_rate, label = dataset[i] plot_specgram(waveform, sample_rate, title=f"Sample {i}: {label}") IPython.display.Audio(waveform, rate=sample_rate)
i = 5 waveform, sample_rate, label = dataset[i] plot_specgram(waveform, sample_rate, title=f"Sample {i}: {label}") IPython.display.Audio(waveform, rate=sample_rate) i = 5 waveform, sample_rate, label = dataset[i] plot_specgram(waveform, sample_rate, title=f"Sample {i}: {label}") IPython.display.Audio(waveform, rate=sample_rate)
- Sample 5: [0, 0, 1, 0, 0, 1, 1, 1]
- Sample 5: [0, 0, 1, 0, 0, 1, 1, 1]
Total running time of the script: (0 minutes 3.885 seconds)