Listen-Attend-Spell-v2 and las-pytorch

Listen-Attend-Spell-v2
40
Emerging
las-pytorch
26
Experimental
Maintenance 0/25
Adoption 7/25
Maturity 16/25
Community 17/25
Maintenance 0/25
Adoption 8/25
Maturity 8/25
Community 10/25
Stars: 39
Forks: 8
Downloads: —
Commits (30d): 0
Language: Shell
License: MIT
Stars: 42
Forks: 4
Downloads: —
Commits (30d): 0
Language: Python
License: —
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About Listen-Attend-Spell-v2

foamliu/Listen-Attend-Spell-v2

PyTorch implementation of Listen Attend and Spell Automatic Speech Recognition (ASR).

This project offers a foundational system for converting spoken Chinese Mandarin into written text. You provide audio recordings in Mandarin, and it produces a transcript of what was said. Researchers and developers working on speech recognition systems for Mandarin would find this useful for building or experimenting with new models.

speech-to-text Mandarin-speech-recognition audio-processing natural-language-processing AI-research

About las-pytorch

jiwidi/las-pytorch

Listen, Attend and spell model for E2E ASR. Implementation in Pytorch

This project offers a foundational implementation for converting spoken language into written text using deep learning. It takes raw audio files as input and outputs a sequence of predicted letters, aiming to transcribe speech accurately. Researchers and engineers working on speech-to-text systems or exploring deep learning architectures for audio processing would find this useful for experimentation and model development.

Speech Recognition Natural Language Processing Deep Learning Audio Processing Machine Learning Research

Related comparisons

Listen-Attend-Spell-v2 and Listen-Attend-Spell Listen-Attend-Spell-v2 and LAS-Pytorch Listen-Attend-Spell-v2 and LAS_Mandarin_PyTorch Listen-Attend-Spell-v2 and Listen-Attend-Spell Listen-Attend-Spell-v2 and LAS-Pytorch

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