TeaPoly/cat_tensorflow

Crf-based Asr Toolkit with TensorFlow implement

28
/ 100
Experimental

This toolkit helps speech researchers and machine learning engineers train custom Automatic Speech Recognition (ASR) acoustic models. It takes audio data and corresponding text transcripts to produce a trained model that can convert spoken language into written text. This is designed for practitioners who need to develop and fine-tune ASR systems, particularly those using Conditional Random Fields (CRF) and TensorFlow.

No commits in the last 6 months.

Use this if you are a speech researcher or machine learning engineer focused on developing high-performance ASR acoustic models using TensorFlow and CRF, and you are comfortable with configuring CUDA environments.

Not ideal if you are looking for an out-of-the-box ASR solution or a tool that doesn't require deep technical knowledge of TensorFlow, CUDA, and ASR model training pipelines.

Automatic Speech Recognition ASR model training speech processing acoustic modeling natural language processing
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 16 / 25

How are scores calculated?

Stars

8

Forks

6

Language

Python

License

Last pushed

Aug 16, 2020

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/voice-ai/TeaPoly/cat_tensorflow"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.