Foundational Model for Speech Recognition Tasks
$ git clone https://github.com/salute-developers/GigaAM.gitEasy-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.
speech to text with self-supervised learning based on wav2vec 2.0 framework
Wav2Vec for speech recognition, classification, and audio classification
Phoneme Recognition using pre-trained models Wav2vec2, HuBERT and WavLM. Throughout this project, we compared specifically three different self-supervised models, Wav2vec (2019, 2020), HuBERT (2021) and WavLM (2022) pretrained on a corpus of English speech that we will use in various ways to perform phoneme recognition for different languages with a network trained with Connectionist Temporal Classification (CTC) algorithm.
Data from GitHub · snapshot Sep 24, 2026