Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

Self-Supervised Speech Pre-training and Representation Learning Toolkit

How to use our public wav2vec2 dimensional emotion model

A live speech recognition using Facebooks wav2vec 2.0 model.

Python API & command-line tool to easily transcribe speech-based video files into clean text

🎤📄 An innovative tool that transforms audio or video files into text transcripts and generates concise meeting minutes. Stay organized and efficient in your meetings, and get ready for Phase 2 where we'll be open for contributions to enable real-time meeting transcription! 🚀

Official implementation of INTERSPEECH 2021 paper 'Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings'

⚡ Finetune Wa2vec 2.0 For Speech Recognition

End-to-End Vietnamese Speech Recognition using wav2vec 2.0

Pytorch implementation of Noisy Student Training for Automatic Speech Recognition and Automatic Pronunciation Error Detection problem

GSoC'2021 | TensorFlow implementation of Wav2Vec2

Solution for Zalo AI Challenge 2022 - Lyrics Alignment

Phoneme segmentation using pre-trained speech models

Scripts used in the research described in the paper "Multimodal Emotion Recognition with High-level Speech and Text Features" accepted in the ASRU 2021 conference.

A mini, simple, and fast end-to-end automatic speech recognition toolkit.

Implementation of the paper "wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations" in Pytorch.

Wav2vec 2.0 Self-Supervised Pretraining

In this project, several approaches for training/finetuning an audio gender recognition is provided. The code can simply be used for any other audio classification task by simply changing the number of classes and the input dataset.

A deep learning lyrics-to-audio alignment system, generating synchronized lyrics from a song and its lyrics

SHAS: Approaching optimal Segmentation for End-to-End Speech Translation