Closed Xuzhejia closed 6 months ago
After preprocessing, you should be able to see training files and its tokens in "lrs3_train_transcript_lengths_seg24s.csv". It should not 0KB.
After preprocessing, you should be able to see training files and its tokens in "lrs3_train_transcript_lengths_seg24s.csv". It should not 0KB.
Not sure if I entered the wrong command Can you give me your command for reference? Thank you.
My problem was in the data_module.py file, which was trying to read an mp4 file and got an error,
waveform, sample_rate = torchaudio.load(data_filename, normalize=True)
causing subsequent steps to be skipped. Is this normal and how can it be resolved?
My problem was in the data_module.py file, which was trying to read an mp4 file and got an error,
waveform, sample_rate = torchaudio.load(data_filename, normalize=True)
causing subsequent steps to be skipped. Is this normal and how can it be resolved? I also found this problem and I'm still looking for a solution.
My problem was in the data_module.py file, which was trying to read an mp4 file and got an error,
waveform, sample_rate = torchaudio.load(data_filename, normalize=True)
causing subsequent steps to be skipped. Is this normal and how can it be resolved? I also found this problem and I'm still looking for a solution.
def load_audio(self, data_filename):
video = VideoFileClip(data_filename)
video.audio.write_audiofile(data_filename[:-1]+"3",logger=None)
waveform, sample_rate = torchaudio.load(data_filename[:-1]+"3", normalize=True)
return waveform, sample_rate
This is my solution.
My problem was in the data_module.py file, which was trying to read an mp4 file and got an error,
waveform, sample_rate = torchaudio.load(data_filename, normalize=True)
causing subsequent steps to be skipped. Is this normal and how can it be resolved? I also found this problem and I'm still looking for a solution.def load_audio(self, data_filename): video = VideoFileClip(data_filename) video.audio.write_audiofile(data_filename[:-1]+"3",logger=None) waveform, sample_rate = torchaudio.load(data_filename[:-1]+"3", normalize=True) return waveform, sample_rate
This is my solution.
def load_audio(self, data_filename):
probe = ffmpeg.probe(data_filename)
process = (
ffmpeg.input(data_filename)
.output('-', format='wav', acodec='pcm_s16le', ar='16000')
.run_async(pipe_stdout=True, quiet=True)
)
stdout, _ = process.communicate()
waveform, sample_rate = torchaudio.load(io.BytesIO(stdout), normalize=True)
return waveform, sample_rate
This also works
What result should be obtained under normal circumstances after preprocessing? Currently I only have a 0KB file called lrs3_train_transcript_lengths_seg24s.csv. Is this correct?