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From the paper, the training data is surprisingly small: "We train all models on an internal US English dataset, which contains 24.6 hours of speech from
by heinrichf 9y ago
From the paper, the training data is surprisingly small:
"We train all models on an internal US English dataset, which contains 24.6 hours of speech from a single professional female speaker."
- mhh__ 9y agoUncompressed, that's still quite a lot of data - perhaps not relative to other ML projects, but still.
- 21 9y agoThey say they split the audio in "80-dimensional audio spectrogram with frames computed every 12.5 milliseconds". The picture from the post supports that. For 24 hours that would be 7 mil frames of 80 values ~= 500 mil data points, or 2 GB of raw data (assuming floats)
- PeterisP 9y agoSo, something that easily fits into RAM, One might even keep a copy of the whole dataset in GPU memory to avoid copying to and from even if matrix operations are done on smaller batches. E.g. ImageNet is 50 gb of compressed data, and there are many much larger datasets in practical use.