Performance estimation of noisy speech recognition using spectral distortion and SNR of noise-reduced speech

Guo Ling, Takeshi Yamada, Shoji Makino, Nobuhiko Kitawaki

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

3 Citations (Scopus)

Abstract

To ensure a satisfactory QoE (Quality of Experience) and facilitate system design in speech recognition services, it is essential to establish a method that can be used to efficiently investigate recognition performance in different noise environments. Previously, we proposed a performance estimation method using the PESQ (Perceptual Evaluation of Speech Quality) as a spectral distortion measure. However, there is the problem that the relationship between the recognition performance and the distortion value differs depending on the noise reduction algorithm used. To solve this problem, we propose a novel performance estimation method that uses an estimator defined as a function of the distortion value and the SNR (Signal to Noise Ratio) of noise-reduced speech. The estimator is applicable to different noise reduction algorithms without any modification. We confirmed the effectiveness of the proposed method by experiments using the AURORA-2J connected digit recognition task and four different noise reduction algorithms.

Original languageEnglish
Title of host publication2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013 - Conference Proceedings
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013 - Xi'an, Shaanxi, China
Duration: 2013 Oct 222013 Oct 25

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Conference

Conference2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013
CountryChina
CityXi'an, Shaanxi
Period13/10/2213/10/25

Keywords

  • noise reduction
  • noisy speech recognition
  • performance estimation
  • SNR
  • spectral distortion

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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