🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.

"Google Now" style animation for Speech Recognizer.

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.

Trained models for automatic speech recognition (ASR). A library to quickly build applications that require speech to text conversion.

A pytorch based end2end speech recognition system.

react-native-android-voice is a speech-to-text library for React Native for the Android Platform.

👄 Java-Speech-Recognizer-Tutorial--Calculator

End-to-end Solution for Speech Recognition, Text Translation, and Text-to-Speech for iOS using Amazon Translate and Amazon Polly as AWS Machine Learning managed services.

Built a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline.

It recognize your speech and trained AI Bot will respond(i.e Customer Service, Personal Assistant) using Machine Learning API (DialogFlow, apiai), Speech Recognition, GraphQL, Next.js, React, redux

A speech recognizer that can run on the browser, inspired by vosk-browser

Transformer-based online speech recognition system with TensorFlow 2

An application that demostrate the usage of Syn.Speech library for Speech Recognition

Example python scripts to evaluate various ASR methods

Speech to text using jetpack compose

Recognize English speech then convert it to text then generate a SQL query from it and then finally fetch data from database

The Conversational Flow combines both native built-in resources and cloud services into a software component capable to run reliably a Speech Synthesizer and a Voice Recognizer.

S.C.A.R.L.E.T (Sorta Crappy Assistant Robot Lazily Engineered Today) To be honest making up that acronym was easier than making this virtual assistant.'She' obeys some of the following commands:search + (what you want to search for),email-opens Gmail.What time is it?What date is it?Youtube-opens Youtube,shut down,Scarlet (check for responsivenes…

Automatic Speech Recognition (ASR) system was implemented using the HMM toolkit for building HMM model using training data. Then, this trained HMM Model was used for recognising words and results revealed that 80.02% accuracy for Phoneme Level Acoustic Model and 79.36% accuracy for word Level Acoustic Model. This developed system can be used by …

Some approaches based on deep learning to build the acoustic model for an end-to-end automatic speech recognition (ASR) pipeline.