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Author Guo Ling ♦ Yamada, T. ♦ Makino, S. ♦ Kitawaki, N.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2013
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Speech ♦ Signal to noise ratio ♦ Accuracy ♦ Speech recognition ♦ Noise reduction ♦ Estimation ♦ SNR ♦ performance estimation ♦ noisy speech recognition ♦ noise reduction ♦ spectral distortion
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.
Description Author affiliation: Grad. Sch. of Syst. & Inf. Eng., Univ. of Tsukuba, Tsukuba, Japan (Guo Ling; Yamada, T.; Makino, S.; Kitawaki, N.)
ISBN 9781479928255
ISSN 21593450
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-10-22
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781479928279
Size (in Bytes) 615.77 kB
Page Count 4
Starting Page 1
Ending Page 4

Source: IEEE Xplore Digital Library