Search results
A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.
Speech Recognition with Python. This repository contains resources from The Ultimate Guide to Speech Recognition with Python tutorial on Real Python. Audio files for the examples in the Working With Audio Files section of the post can be found in the audio_files directory.
SpeechRecognition. Library for performing speech recognition, with support for several engines and APIs, online and offline. UPDATE 2022-02-09: Hey everyone! This project started as a tech demo, but these days it needs more time than I have to keep up with all the PRs and issues.
The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.
Pull requests. This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the same time, this project also supports MelSpectrogram, Spectrogram data preprocessing methods.
Speech Emotion Recognition (SER) in real-time. A Deep Learning (LSTM) model with keras. This study aims to investigate and implement an Artificial Intelligence (AI) algorithm that will analyze an audio file in real-time, identify and present the expressed emotion within it.
We are building solutions to stop harrashment and hate speech in online voice communication
Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification.
The J.A.R.V.I.S. Speech API is designed to be simple and efficient, using the speech engines created by Google to provide functionality for parts of the API. Essentially, it is an API written in Java, including a recognizer, synthesizer, and a microphone capture utility. The project uses Google services for the synthesizer and recognizer. While …
To associate your repository with the speech-emotion-recognition topic, visit your repo's landing page and select "manage topics." Learn more. GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.
