Displaying 1 to 20 from 63 results

DeepSpeech - A TensorFlow implementation of Baidu's DeepSpeech architecture

  •    C

Project DeepSpeech is an open source Speech-To-Text engine. It uses a model trained by machine learning techniques, based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow project to make the implementation easier.

speech_recognition - Speech recognition module for Python, supporting several engines and APIs, online and offline

  •    Python

Library for performing speech recognition, with support for several engines and APIs, online and offline. Quickstart: pip install SpeechRecognition. See the "Installing" section for more details.

HTK - Speech Recognition Toolkit

  •    C

The Hidden Markov Model Toolkit (HTK) is a portable toolkit for building and manipulating hidden Markov models. HTK is primarily used for speech recognition research although it has been used for numerous other applications including research into speech synthesis, character recognition and DNA sequencing. HTK is in use at hundreds of sites worldwide.

tensorflow-speech-recognition - 🎙Speech recognition using the tensorflow deep learning framework, sequence-to-sequence neural networks

  •    Python

Speech recognition using google's tensorflow deep learning framework, sequence-to-sequence neural networks. Replaces caffe-speech-recognition, see there for some background.




Leon - Your open-source personal assistant

  •    Python

Leon is an open-source personal assistant who can live on your server. He does stuff when you ask him for. You can talk to him and he can talk to you. You can also text him and he can also text you. If you want to, Leon can communicate with you by being offline to protect your privacy.

kalliope - Kalliope is a framework that will help you to create your own personal assistant.

  •    Python

Kalliope is a framework that will help you to create your own personal assistant. The concept is to create the brain of your assistant by attaching an input signal (vocal order, scheduled event, MQTT message, GPIO event, etc..) to one or multiple actions called neurons.

annyang - :speech_balloon: Speech recognition for your site

  •    Javascript

A tiny javascript SpeechRecognition library that lets your users control your site with voice commands. annyang has no dependencies, weighs just 2 KB, and is free to use and modify under the MIT license.


NLP-Models-Tensorflow - Gathers machine learning and Tensorflow deep learning models for NLP problems, 1

  •    Jupyter

NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. I will attached github repositories for models that I not implemented from scratch, basically I copy, paste and fix those code for deprecated issues.

lingvo - Lingvo

  •    Python

Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models. A list of publications using Lingvo can be found here.

Kur - Descriptive Deep Learning

  •    Python

Kur is a system for quickly building and applying state-of-the-art deep learning models to new and exciting problems. Kur was designed to appeal to the entire machine learning community, from novices to veterans. It uses specification files that are simple to read and author, meaning that you can get started building sophisticated models without ever needing to code. Even so, Kur exposes a friendly and extensible API to support advanced deep learning architectures or workflows.

CMU Sphinx - Toolkit For Speech Recognition

  •    C

CMUSphinx toolkit is a speech recognition toolkit with various tools used to build speech applications. CMU Sphinx toolkit has a number of packages for different tasks. Pocketsphinx — lightweight recognizer library written in C, Sphinxbase — support library required by Pocketsphinx, Sphinx4 — adjustable, modifiable recognizer written in Java, CMUclmtk — language model tools, Sphinxtrain — acoustic model training tools, Sphinx3 — decoder for speech recognition research written in C.

adapt - Adapt Intent Parser

  •    Python

To take a dependency on Adapt, it's recommended to use virtualenv and pip to install source from github. Executable examples can be found in the examples folder.

Stephanie - Open-source platform built specifically for voice-controlled applications as well as to automate daily tasks imitating much of an virtual assistant's work

  •    Python

Stephanie is an open-source platform built specifically for voice-controlled application as well as to automate daily tasks imitating much of an virtual assistant's work. Use your voice to ask for information, update social networks, get weather updates, live football scores, movies information restaurant suggestions, writing a note, or even chit-chatting for fun, and many more.

STT - The deep learning toolkit for Speech-to-Text

  •    C++

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

voicy - @voicybot Telegram bot main repository

  •    Javascript

This repository contains the code for one of the most popular bots I've ever built for Telegram — @voicybot. Please, feel free to fork, add features and create pull requests so that everybody (over 600 000 chats) can experience the features you've built. You can also help by translating the bot to other languages or fixing some texts in existing languages by modifying the locales folder.

sonus - :speech_balloon: /so.nus/ STT (speech to text) for Node with offline hotword detection

  •    Javascript

Sonus lets you quickly and easily add a VUI (Voice User Interface) to any hardware or software project. Just like Alexa, Google Now, and Siri, Sonus is always listening offline for a customizable hotword. Once that hotword is detected your speech is streamed to the cloud recognition service of your choice - then you get the results. Generally, running npm install should suffice. This module however, requires you to install SoX.

dc_tts - A TensorFlow Implementation of DC-TTS: yet another text-to-speech model

  •    Python

I implement yet another text-to-speech model, dc-tts, introduced in Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention. My goal, however, is not just replicating the paper. Rather, I'd like to gain insights about various sound projects. I train English models and an Korean model on four different speech datasets.

stt-benchmark - speech to text benchmark framework

  •    Python

This is a minimalist and extensible framework for benchmarking different speech-to-text engines. It has been developed and tested on Ubuntu 18.04 with Python3.6. This framework has been developed by Picovoice as part of the project Cheetah. Cheetah is Picovoice's speech-to-text engine specifically designed for IoT applications. Deep learning has been the main driver in recent improvements in speech recognition. But due to stringent compute/storage limitations of IoT platforms it is most beneficial to the cloud-based engines. Picovoice's proprietary deep learning technology enables transferring these improvements to IoT platforms with much lower CPU/memory footprint. The goal is to be able to run Cheetah on any platform with a C Compiler and a few MB of memory.






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