The release of the open speech synthesis system RHVoice 1.6.0 has taken place. Initially developed to provide quality support for the Russian language, it has since been adapted for other languages including English, Portuguese, Ukrainian, Kyrgyz, Tatar, and Georgian. The code is written in C++ and is distributed under the LGPL 2.1 license. It supports operation in GNU/Linux, Windows, and Android. The program is compatible with standard TTS interfaces for converting text to speech: SAPI5 (Windows), Speech Dispatcher (GNU/Linux), and Android Text-To-Speech API, but can also be used in the NVDA screen reader. The creator and main developer of RHVoice is Olga Yakovleva, who continues to develop the project despite being completely blind.
The new version adds 5 new voice options for Russian speech. Support for the Albanian language has been implemented. The Ukrainian language dictionary has been updated. Support for the pronunciation of emoji characters has been expanded. Work has been done to fix bugs in the Android application, user dictionary import has been simplified, and support for Android 11 has been added. New settings and features have been added to the core engine, including g2p.case, word_break, and support for equalization filters.
It should be noted that RHVoice utilizes developments from the HTS project (HMM/DNN-based Speech Synthesis System) and employs a parametric synthesis method with statistical models (Statistical Parametric Synthesis based on HMM — Hidden Markov Model). The advantage of the statistical model is its low overhead and low CPU power demands. All operations are performed locally on the user's system. Three levels of speech quality are supported (the lower the quality, the higher the performance and the lower the response time).
A drawback of the statistical model is its relatively low quality of pronunciation, which does not reach the level of synthesizers that generate speech based on combinations of fragments of natural speech. Nonetheless, the result is quite intelligible and resembles the playback of a recording over a loudspeaker. For comparison, the Silero project, which provides an open engine for speech synthesis based on machine learning technologies and a set of models for the Russian language, surpasses RHVoice in quality.
There are 13 voice options available for the Russian language and 5 for English. The voices are based on recordings of natural speech. In the settings, speed, pitch, and volume can be adjusted. The Sonic library can be used to change the pace. Automatic language detection and switching based on input text analysis is possible (for example, a native synthesis model for the language may be used for words and quotes in another language). Voice profiles are supported, defining combinations of voices for different languages.
Source: opennet.ru
