KrishnaDN/BERTphone

Implementation of the paper "BERTphone: Phonetically-aware Encoder Representations for Utterance-level Speaker and Language Recognition"

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Experimental

This project helps researchers analyze speech by converting raw audio recordings into a format suitable for advanced modeling. It takes spoken language audio as input and produces processed data and extracted speech features. Researchers and scientists working with speech recognition or speaker identification will find this useful.

No commits in the last 6 months.

Use this if you are a researcher working with the TIMIT dataset and need to process audio for speaker or language recognition experiments.

Not ideal if you are looking for a ready-to-use application for general speech analysis or support for datasets other than TIMIT.

speech-research phonetics speaker-recognition language-identification audio-processing
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 15 / 25

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Language

Python

License

Last pushed

Dec 10, 2020

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