audio8
API examples using 8-mile for audio
Implementation
The codebase relies primarily on 8-mile (mead-layers) for its modeling and optimization code.
Whats left is pretty much just training and inference code
Dependencies
The code depends on:
editdistance(for error evaluation)numpysixsoundfilemead-baselinepytorch
There are a few optional dependencies
scipy(for on-the-fly resampling of wav files)ctcdecode(for prefix beam decoding with optional LM)
1 maintainer
Metadata
1 maintainer
Release files for mead-audio8 0.0.6
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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| mead-audio8-0.0.6.tar.gz | 32.7 kB | Without provenance | Details for mead-audio8-0.0.6.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| mead_audio8-0.0.6-py3-none-any.whl | Python 3 | none | any | Details for mead_audio8-0.0.6-py3-none-any.whl |
Total release size: 89.4 kB
Release files / mead-audio8-0.0.6.tar.gz
| Download URL | mead-audio8-0.0.6.tar.gz |
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| Size | 32.7 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / mead_audio8-0.0.6-py3-none-any.whl
| Download URL | mead_audio8-0.0.6-py3-none-any.whl |
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| Size | 56.7 kB |
| Tags | Python 3 |
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