A review-based study on different Text-to-Speech technologies

TL;DR

This paper provides a comprehensive review of various Text-to-Speech technologies, comparing their advantages, limitations, and recent advancements like neural and hybrid TTS to guide future research and application development.

Contribution

It offers a detailed comparison of TTS technologies, including traditional and modern neural approaches, highlighting their respective strengths and limitations.

Findings

Neural TTS offers more natural voice quality.

Concatenative TTS is simpler but less flexible.

Hybrid TTS combines advantages of multiple methods.

Abstract

This research paper presents a comprehensive review-based study on various Text-to-Speech (TTS) technologies. TTS technology is an important aspect of human-computer interaction, enabling machines to convert written text into audible speech. The paper examines the different TTS technologies available, including concatenative TTS, formant synthesis TTS, and statistical parametric TTS. The study focuses on comparing the advantages and limitations of these technologies in terms of their naturalness of voice, the level of complexity of the system, and their suitability for different applications. In addition, the paper explores the latest advancements in TTS technology, including neural TTS and hybrid TTS. The findings of this research will provide valuable insights for researchers, developers, and users who want to understand the different TTS technologies and their suitability for specific applications.