Audio Speech Tutorial Alternatives

This repository contains a short introduction on the topic of audio and speech processing -- from basics to applications.
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Alternatives To koudounasalkis/Audio-Speech-Tutorial
Project Name Stars Downloads Repos Using This Packages Using This Most Recent Commit Total Releases Latest Release Open Issues License Language
speechbrain/speechbrain 7,166 0 0 about 2 years ago 0 149 apache-2.0 Python
A PyTorch-based Speech Toolkit
EmulationAI/awesome-large-audio-models 207 0 0 over 2 years ago 0 0
Collection of resources on the applications of Large Language Models (LLMs) in Audio AI.
gtreshchev/RuntimeSpeechRecognizer 153 0 0 about 2 years ago 0 2 mit C++
Cross-platform, real-time, offline speech recognition plugin for Unreal Engine. Based on Whisper OpenAI technology, whisper.cpp.
Picovoice/web-voice-processor 147 4 26 about 2 years ago 39 March 15, 2024 4 apache-2.0 TypeScript
A library for real-time voice processing in web browsers
Carleslc/AudioToText 132 0 0 about 2 years ago 0 1 Jupyter Notebook
Transcribe and translate audio to text using Whisper and DeepL.
pszemraj/vid2cleantxt 53 0 0 over 3 years ago 2 February 24, 2022 0 apache-2.0 Jupyter Notebook
Python API & command-line tool to easily transcribe speech-based video files into clean text
rioharper/VocalForge 39 0 0 over 2 years ago 8 July 20, 2023 0 mit Python
Your one-stop solution for voice dataset creation
koudounasalkis/Audio-Speech-Tutorial 12 0 0 over 2 years ago 0 0 mit Jupyter Notebook
This repository contains a short introduction on the topic of audio and speech processing -- from basics to applications.
balavenkatesh3322/audio-pretrained-model 11 0 0 over 5 years ago 0 0 mit
A collection of Audio and Speech pre-trained models.
victor369basu/End2EndAutomaticSpeechRecognition 7 0 0 almost 5 years ago 0 0 Python
In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
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