: NLP Vocabulary: text-to-speech

applied NLP > speech processing > text-to-speech

text-to-speech

Text-to-speech synthesis (TTS) generates speech from text and is an important task with wide applications in dialog systems speech translation natural language user interface assistive technologies etc. (Ma, Zheng, Liu, Zheng, Liu, Peng, Church & Huang, 2020)
Text-to-Speech (TTS) synthesis is a process which artificially produces synthetic speech for various applications such as services over telephone e-document reading and speaking system for handicapped people etc. (Anberbir & Takara, 2009)
Text-to-Speech (TTS) synthesis is a technology that transforms written text into its spoken equivalent thereby enhancing content accessibility. (Feng & Yoshimoto, 2024)

A Text-To-Speech (TTS) system converts given language text into speech. (Zhang, Yuan, Chen, Li, Zheng, Huang, Chen, Gong, Chen, Hu, Yu, Ma & Huang, 2022)
Currently listening exercises are not available for Sakha; we plan to incorporate them into the system when text-to-speech (TTS) synthesis for Sakha becomes available. (Ivanova, Katinskaia & Yangarber, 2019)
Text-to-speech synthesis (TTS) consists of a number of processing steps that control the conversion of input text to output speech. (Tyagi, Bonafonte, Lorenzo-Trueba & Latorre, 2021)
Text-To-Speech (TTS) systems can only be evaluated effectively using the mean opinion score (MOS) and degradation mean opinion score (DMOS) as recommended metrics for synthesized speech quality. (Gupta, 2023)
Thus in order to make text-to-speech synthesis sound as natural and engaging as possible it is important to convey the emotional stance in the text. (Alm, Roth & Sproat, 2005)

http://data.loterre.fr/ark:/67375/8LP-P3RN8DP4-K

RDF/XML TURTLE JSON-LD Last modified 5/2/24

Loterre