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

Research output: Contribution to journalArticle

Details

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalCOMPUTER SPEECH AND LANGUAGE
Volume53
StatePublished - 1 Jan 2019
MoE publication typeA1 Journal article-refereed

Researchers

Research units

  • University of Eastern Finland

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.

    Research areas

  • Shouted speech, Speaker recognition, Vocal effort mismatch

ID: 27113854