Earticle

초록

영어

In this paper, a hidden Markov model (HMM) based distributed text-to-speech (TTS) system is proposed to synthesize the voices of various speakers in a client-server framework. The proposed system is based on speaker-adaptive training for constructing HMMs corresponding to a target speaker, and its computational complexity is balanced by distributing the processing modules of the TTS system at both the client and server to achieve a real-time operation. In other words, fewer complex operations, such as text inputs and HMM-based speech synthesis, are conducted by the client, while speaker-adaptive training, which is a very complex operation, is assigned to the server. It is shown from performance evaluation that the proposed TTS system operates in real time and provides good synthesized speech quality in terms of intelligibility and similarity.

목차

Abstract
 1. Introduction
 2. HMM-Based TTS System with Speaker-Adaptive Training
 3. Proposed HMM-Based Distributed TTS System
  3.1. Voice Cloning Stage
  3.2. Speech Synthesis Stage
 4. Performance Evaluation
  4.1. Evaluation of Voice Cloning Stage
  4.2. Evaluation of Speech Synthesis Stage
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Kwang Myung Jeon [ School of Information and Communications Gwangju Institute of Science and Technology, Gwangju 500-712, Korea ]
• Seung Ho Choi [ Dept. of Electronic and IT Media Engineering Seoul National University of Science and Technology, Seoul 139-743, Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605