Speech enhancement using a state-based transform model

Michael E. Deisher, Andreas Spanias

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

Abstract

An analysis/synthesis technique based on harmonic sinusoidal modeling of speech is used to develop a new hidden Markov model (HMM) based speech enhancement algorithm. State sequence estimation is done using a standard HMM-based approach. State-based enhancement is carried out by assuming a harmonic model for speech, i.e., by representing each block of speech as a sum of sine waves in terms of a set of amplitudes, phases, and harmonically related frequencies. Given the maximum a-posteriori probability (MAP) state sequence, the amplitudes, phases, voicing, and fundamental frequency are estimated. Simulation results are presented, comparing the performance of the proposed algorithm to that of a standard HMM-based approach. The proposed method was found to reduce the structured residual noise normally associated with HMM-based algorithms.

Original languageEnglish (US)
Title of host publicationConference Record - 28th Asilomar Conference on Signals, Systems and Computers, ACSSC 1994
PublisherIEEE Computer Society
Pages1242-1246
Number of pages5
ISBN (Electronic)0818664053
DOIs
StatePublished - Jan 1 1994
Event28th Asilomar Conference on Signals, Systems and Computers, ACSSC 1994 - Pacific Grove, United States
Duration: Oct 31 1994Nov 2 1994

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2
ISSN (Print)1058-6393

Conference

Conference28th Asilomar Conference on Signals, Systems and Computers, ACSSC 1994
CountryUnited States
CityPacific Grove
Period10/31/9411/2/94

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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