There are 3 repositories under wav2vec2 topic.
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.
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
Official implementation of INTERSPEECH 2021 paper 'Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings'
:zap: Finetune Wa2vec 2.0 For Speech Recognition
GSoC'2021 | TensorFlow implementation of Wav2Vec2
Pytorch implementation of Noisy Student Training for Automatic Speech Recognition and Automatic Pronunciation Error Detection problem
Solution for Zalo AI Challenge 2022 - Lyrics Alignment
🎤📄 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! 🚀
Phoneme segmentation using pre-trained speech models
A mini, simple, and fast end-to-end automatic speech recognition toolkit.
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.
fine-tune Wav2vec2. an ASR model released by Facebook
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.
real time japanese speech recognition translator using wav2vec2
Wav2vec resources and models for Brazilian Portuguese
[ICASSP 2023] Mingling or Misalignment? Temporal Shift for Speech Emotion Recognition with Pre-trained Representations
This app is intended to automatically create a corpus for ASR systems using pseudo-labeling.
Wav2vec 2.0 Self-Supervised Pretraining
Simple Python library, distributed via binary wheels with few direct dependencies, for easily using wav2vec 2.0 models for speech recognition
Preschool evaluation is crucial because it gives teachers and parents influential knowledge about children's growth and development. The COVID-19 pandemic has highlighted the necessity of online assessment for preschool children. One of the areas that should be tested is their ability to speak. Employing an Automatic Speech Recognition (ASR) system would not help since they are pre-trained on voices that differ from children's in terms of frequency and amplitude. Because most of these are pre-trained with data in a specific range of amplitude, their objectives do not make them ready for voices in different amplitudes. To overcome this issue, we added a new objective to the masking objective of the Wav2Vec 2.0 model called Random Frequency Pitch (RFP). In addition, we used our newly introduced dataset to fine-tune our model for Meaningless Words (MW) and Rapid Automatic Naming (RAN) tests. Using masking in concatenation with RFP outperforms the masking objective of Wav2Vec 2.0 by reaching a Word Error Rate (WER) of 1.35. Our new approach reaches a WER of 6.45 on the Persian section of the CommonVoice dataset. Furthermore, our novel methodology produces positive outcomes in zero- and few-shot scenarios.
An ASR (Automatic Speech Recognition) adversarial attack repository.
Implementation of the paper "wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations" in Pytorch.
Recognize speech from an audio file and convert it into animation FBX
Turkish Speech Recognition using Facebook's Wav2vec 2.0 models
Audio Preprocessing and finetuning of wav2vec2-large-xlsr model on AI4D Baamtu Datamation - Automatic Speech Recognition in WOLOF Data.
Cantonese Selfish Project 廣東話自肥企劃 at PYCON HK 2021
Adnabod lleferydd Cymraeg i'r Gymraeg gyda HuggingFace // Speech Recognition for Welsh with HuggingFace
A system capable of converting Nepali speech to text and generate summary of text
A deep learning lyrics-to-audio alignment system, generating synchronized lyrics from a song and its lyrics
Speeech Recognition for Indic languages.