Problem with loading rawwav as feature, it costs too much time

[liuzz13]

Hi
Recently, I did some experiments with pytorch-kaldi. I find that it cost too much time to load data when using raw wav as feature, even more than training time. Do we have a batter dataloader? Or how can I reduce the time to load data?

[mravanelli]

Yes, we are aware of it. That's because the toolkit is designed to read features in kaldi format rather than waveforms. For the speechbrain project we are developing a totally new dataloader that can read any kind of features (including waveforms) in a very very fast way. Best, Mirco

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On Sun, 9 Feb 2020 at 08:37, liuzz13 ***@***.***> wrote: Hi Recently, I did some experiments with pytorch-kaldi. I find that it cost too much time to load data when using raw wav as feature, even more than training time. Do we have a batter dataloader? Or how can I reduce the time to load data? — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#212?email_source=notifications&email_token=AEA2ZVXQ237AU7OB67ECWRLRCABLNA5CNFSM4KSBWZT2YY3PNVWWK3TUL52HS4DFUVEXG43VMWVGG33NNVSW45C7NFSM4IMCFAYQ>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AEA2ZVSJDPVC5YH2GQ2SERTRCABLNANCNFSM4KSBWZTQ> .

[lezasantaizi]

Hi
Recently, I did some experiments with pytorch-kaldi. I find that it cost too much time to load data when using raw wav as feature, even more than training time. Do we have a batter dataloader? Or how can I reduce the time to load data?

transform wav to feature