Open Source Python Speech Software

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. If you want to use the pre-trained English model for performing speech-to-text, you can download it (along with other important inference material) from the DeepSpeech releases page.

Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using pip install SpeechRecognition. The first software requirement is Python 2.6, 2.7, or Python 3.3+. This is required to use the library. PyAudio is required if and only if you want to use microphone input (Microphone). PyAudio version 0.2.11+ is required, as earlier versions have known memory management bugs when recording from microphones in certain situations. To hack on this library, first make sure you have all the requirements listed in the "Requirements" section.

Just log your favorite FM station speech to a text file using rtl-sdr dongle and speech recognition. Cross-platform tool. Follow the README on the download page for Windows installation. https://sourceforge.net/projects/fm2txt-rtlsdr/files/ If you prefer GitHub source, not SF: https://github.com/randaller/fm2txt For those, who want to recognize from soundcard, not from rtl-sdr (this allows to transcribe NFM etc): https://github.com/randaller/souncard2txt

Sayz Me is a text-to-speech application for Windows. Text can be typed in or read from clipboard. Words are highlighted when spoken. Select voice, adjust reading speed, voice pitch, font and color. Simple and easy to use.

An extensible (by plugin) chatbot project

AarTon is an automated text-to-speech application. It allows user to enter text in a web-based front-end and render these texts via a multi-channel sound card.

This software design to convert text to speech and download the converted speech. Description : • Installation setup with two languages (English, French) • Two areas called text reading and speech downloading • Many languages supported to download center Note 1: I'm a student yet and I'm not in the software designing industry. Therefore maybe I haven't software making skills. I'm worried about that. ! Note 2 : When you double click on the software maybe it will get some seconds to open. That's not my fault. I used Python language to make this software and Python was not supported speedy to modern computers.

Eve is a AI project written in python that takes commands verbally or textually to control the computer and eveyday functions.

InproTK is an Incremental Spoken Dialogue Processing Toolkit, that is, a toolkit to help you build dialogue systems that listen and talk incrementally, allowing for advanced interactional behaviour. Please see our Wiki for more information: http://sourceforge.net/p/inprotk/wiki/

RNNLIB is a recurrent neural network library for sequence learning problems. Applicable to most types of spatiotemporal data, it has proven particularly effective for speech and handwriting recognition. full installation and usage instructions given at http://sourceforge.net/p/rnnl/wiki/Home/

Speect is a multilingual TTS system. It offers a full text-to-speech system with various API's, as well as an environment for research and development of TTS systems and voices. It is written in ANSI C and uses a plug-in mechanism for extensions. Speect also includes an extensive set of Python bindings for quick implementation of new ideas, these bindings are derived from SWIG interface files and can easily be extended for other languages supported by SWIG. Speect is free and open source software. As a collection it is distributed under a MIT license.

Steel is a cross-platform package for using common text-to-speech (speech synthesis) engines in Python. Steel currently supports the following TTS software: - Microsoft Speech API 5 (SAPI5) - eSpeak - NS Speech Synthesis - FreeTTS Documentation: http://sourceforge.net/p/steeltts/wiki/ Bug Tracker: http://sourceforge.net/p/steeltts/tickets/ If you are interested in contributing to the Steel TTS codebase, or would like to make a feature-request, please contact the lead developer, Jasper Danielson, at jrd4@rice.edu.

Software to fit whole-sentence language models using the principle of maximum entropy. For developers of speech recognizers, text prediction interfaces, OCR, machine translation software.

uListen is a TTS(Text To Speech) application. It can TALK you the web pages, chm files, pdf files and word files and plain text files.