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I'm wondering if there's a more efficiet way of handling large datasets in Lhotse similarly to HuggingFace datasets? I can see that datasets consisting of potentially millions of audio files can put strain on the network FS and slow down the data transfer. Also, moving such datasets around can be quite complicated.
I know that Lhotse supports a compressed format shar but it's not suitable for random access during training afaik.
Do you think including support for something like Apache Arrows would be a good idea? This way, one would be able to convert the entire dataset (at least the audio files) into a few shard files and still access the individual files randomly without a significant performance loss.
Thanks for the response.
Best,
Dominik
The text was updated successfully, but these errors were encountered:
domklement
changed the title
Manipulating with large amounts of Wavs
Manipulating large amounts of Wavs
Feb 13, 2025
Hello,
I'm wondering if there's a more efficiet way of handling large datasets in Lhotse similarly to HuggingFace datasets? I can see that datasets consisting of potentially millions of audio files can put strain on the network FS and slow down the data transfer. Also, moving such datasets around can be quite complicated.
I know that Lhotse supports a compressed format
shar
but it's not suitable for random access during training afaik.Do you think including support for something like
Apache Arrows
would be a good idea? This way, one would be able to convert the entire dataset (at least the audio files) into a few shard files and still access the individual files randomly without a significant performance loss.Thanks for the response.
Best,
Dominik
The text was updated successfully, but these errors were encountered: