Neural Speech Synthesis


Neural speech synthesis is a technology that uses artificial neural networks to generate synthesized speech. It is a type of text-to-speech (TTS) technology that is based on machine learning techniques and can produce more natural-sounding speech than traditional TTS systems.

Neural speech synthesis systems are trained on large datasets of speech recordings and text transcripts, and use machine learning algorithms to learn the patterns and relationships between text and speech. When given a text input, a neural speech synthesis system can generate synthesized speech that is designed to sound similar to the way a human would speak the same text.

Neural speech synthesis is used for a variety of purposes, including generating synthesized speech for use in voice assistants, automated customer service systems, and other applications where natural-sounding speech is desired. It is also used in research and development for speech and language processing, and in the development of assistive technologies for people with disabilities.



See also:

Speech Synthesis Meta Guide

[18x Sep 2021]

  • as-ideas/transformertts .. transformer tts: implementation of a non-autoregressive transformer based neural network for text to speech.
  • cpuimage/transformer-tts .. a tensorflow implementation like “neural speech synthesis with transformer network” port from openseq2seq
  • mozilla/tts .. :robot: :speech_balloon: deep learning for text to speech (discussion forum: