Enhancement of spectral clarity for HMM-based text-to-speech systems

Young Sun Joo, Chi Sang Jung, Hong Goo Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a method to enhance the spectral clarity of hidden Markov model (HMM)-based text-to-speech (TTS) systems. A simple way of enhancing spectral clarity is increasing the order of spectral parameters in the speech analysis/synthesis stage, but the method has an inherent statistical modeling problem. The proposed algorithm takes a low-to-high-order spectral parameter mapping approach that adopts low-order parameters for HMM training but does high-order parameters for the actual synthesis step. Various ways of mapping criterion to find appropriate high-order parameters are investigated to further enhance the quality of synthesized speech. Performance evaluation results verify the superiority of the proposed method compared to the conventional one.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages7840-7843
Number of pages4
DOIs
Publication statusPublished - 2013 Oct 18
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 2013 May 262013 May 31

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period13/5/2613/5/31

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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