Open-source softwareSpeech processingA modular and extensible end-to-end Korean automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch called as KoSpeech was released as an opensource software. Several ASR open-source toolkits have been released, but all of them deal...
speech processingopen source softwareCreating of speech recognition application requires advanced speech processing techniques realized by specialized speech processing software. It is very possible to improve the speech recognition research by using frameworks based on open source speech processing software. ...
Kõnele service is an Android app that offers a speech-to-text service to other apps, in particular to Kõnele. It implements SpeechRecognizer, backed by an open source speech recognition server software https://github.com/alumae/kaldi-gstreamer-serv
RHVoice is a free and open-source speech synthesizer. Features Speech synthesis method RHVoice uses statistical parametric synthesis. It relies on existing open-source speech technologies (mainly HTS and related software). Voices are built from recordings of natural speech. They have small footprints,...
What is open source speech synthesis, and how does it work? Here is everything you need to know about this technology.
1983. Programmer Richard Stallman chafed at the notion that users could not customize proprietary software however they saw fit to accomplish their work. Stallman felt that “software should be free—as in speech, not beer” and he championed the notion of freely available software for ...
CMUSphinx-Open Source Toolkit For Speech Recognition http://cmusphinx.sourceforge.net/wiki/ 可以从上面学习一些概念,比如: Models According to the speech structure, three models are used in speech recognition to do the match: Anacoustic modelcontains acoustic properties for each senone. There are ...
eSpeakis a compact open-source software speech synthesizer for English and other languages, for Linux and Windows. eSpeak uses a "formant synthesis" method. This allows many languages to be provided in a small size. The speech is clear, and can be used at high speeds, but is not as nat...
Part of the ESPnet project, this TTS engine is designed for end-to-end speech processing, including both speech recognition and synthesis. It uses modern deep-learning techniques to generate speech. Pros: Modern and flexible, supports multiple languages. Cons: Requires some technical knowledge to ...
Speech recognition has been increasingly used on mobile devices, which has in turn increased the need for creation of new acoustic models for various languages, dialects, accents, speakers and environmental conditions. This involves training and adapting a huge number of acoustic models, some of ...