George0828Zhang/torch_cif

A fast parallel PyTorch implementation of the "CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition" https://arxiv.org/abs/1905.11235.

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This tool helps researchers and machine learning engineers working on speech recognition systems. It takes raw speech features and their corresponding firing probabilities to produce integrated speech features, representing recognized speech units. Its primary users are those developing or experimenting with end-to-end speech recognition models.

No commits in the last 6 months. Available on PyPI.

Use this if you are implementing or researching speech recognition models and need a fast, parallel way to convert continuous speech features into discrete output units using the Continuous Integrate-and-Fire (CIF) mechanism.

Not ideal if you are a casual user looking for a ready-to-use speech-to-text application or do not have experience with PyTorch and deep learning.

speech-recognition audio-processing deep-learning-research natural-language-processing
Stale 6m
Maintenance 0 / 25
Adoption 7 / 25
Maturity 25 / 25
Community 11 / 25

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Stars

36

Forks

4

Language

Python

License

MIT

Last pushed

Feb 10, 2024

Commits (30d)

0

Dependencies

1

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