Displaying 1 to 20 from 46 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.


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.

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.

OpenSeq2Seq - Toolkit for efficient experimentation with various sequence-to-sequence models

  •    Python

This is a research project, not an official NVIDIA product. OpenSeq2Seq main goal is to allow researchers to most effectively explore various sequence-to-sequence models. The efficiency is achieved by fully supporting distributed and mixed-precision training. OpenSeq2Seq is built using TensorFlow and provides all the necessary building blocks for training encoder-decoder models for neural machine translation and automatic speech recognition. We plan to extend it with other modalities in the future.

nodejs-speech - Node

  •    Javascript

The Cloud Speech API enables easy integration of Google speech recognition technologies into developer applications. Send audio and receive a text transcription from the Cloud Speech API service. Select or create a Cloud Platform project.

react-native-speech - A text-to-speech library for React Native.

  •    Objective-C

React Native Speech is a text-to-speech library for React Native. In order to use Speech, you must first link the library your project. There's excellent documentation on how to do this in the React Native Docs.

Phonetisaurus - Phonetisaurus G2P

  •    Python

This repository contains scripts suitable for training, evaluating and using grapheme-to-phoneme models for speech recognition using the OpenFst framework. The current build requires OpenFst version 1.6.0 or later, and the examples below use version 1.6.2. The repository includes C++ binaries suitable for training, compiling, and evaluating G2P models. It also some simple python bindings which may be used to extract individual multigram scores, alignments, and to dump the raw lattices in .fst format for each word.