tensorflow_end2end_speech_recognition and tensorflow-ctc-speech-recognition

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 22/25
Stars: 314
Forks: 119
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 131
Forks: 47
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About tensorflow_end2end_speech_recognition

hirofumi0810/tensorflow_end2end_speech_recognition

End-to-End speech recognition implementation base on TensorFlow (CTC, Attention, and MTL training)

This project helps researchers and developers build custom speech recognition systems. It takes audio recordings from popular speech datasets like TIMIT, LibriSpeech, or CSJ, and processes them to output text transcripts. It's designed for someone specializing in machine learning or natural language processing who needs to experiment with advanced end-to-end speech recognition models.

speech-to-text natural-language-processing machine-learning-research audio-transcription voice-technology

About tensorflow-ctc-speech-recognition

philipperemy/tensorflow-ctc-speech-recognition

Application of Connectionist Temporal Classification (CTC) for Speech Recognition (Tensorflow 1.0 but compatible with 2.0).

This project helps speech technologists and researchers convert spoken audio into written text using a neural network approach. You provide audio files of someone speaking, and it attempts to transcribe those words into a written transcript. It's designed for those exploring or implementing speech recognition systems, particularly with Connectionist Temporal Classification (CTC).

speech-to-text audio-transcription natural-language-processing acoustic-modeling voice-technology

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