Vocal effort compensation for MFCC feature extraction in a shouted versus normal speaker recognition task

Emma Jokinen*, Rahim Saeidi, Tomi Kinnunen, Paavo Alku

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)
3 Downloads (Pure)

Abstract

In shouting, speakers use increased vocal effort to convey spoken messages over distance or above environmental noise. For automatic speaker recognition systems trained using normal speech, shouting causes a severe vocal effort mismatch between the enrollment and test hence reducing the recognition performance. In this study, two compensation methods are proposed to tackle the mismatch in a shouted versus normal speaker recognition task. These techniques are applied in the feature extraction stage of a speaker recognition system to modify the spectral envelopes of shouts to be closer to those in normal speech. The techniques modify the all-pole power spectrum of the MFCC computation chain with shouted-to-normal compensation filtering that is obtained using a GMM-based statistical mapping. In an evaluation using the state-of-the-art i-vector based recognition system, the proposed techniques provided considerable improvements in identification rates compared to the case when shouted speech spectra were not processed.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalComputer Speech and Language
Volume53
DOIs
Publication statusPublished - 1 Jan 2019
MoE publication typeA1 Journal article-refereed

Keywords

  • Shouted speech
  • Speaker recognition
  • Vocal effort mismatch

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    Interdisciplinary research on statistical parametric speech synthesis

    Juvela, L., Airaksinen, M., Bollepalli, B., Bäckström, T., Pohjalainen, J., Kakouros, S., Gowda, D., Jokinen, E. & Alku, P.

    01/01/201531/12/2017

    Project: Academy of Finland: Other research funding

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    Science-IT

    Mikko Hakala (Manager)

    School of Science

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