TeaPoly/cat_tensorflow
Crf-based Asr Toolkit with TensorFlow implement
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.
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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.
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Python
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Last pushed
Aug 16, 2020
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