English sentence recognition in speech-shaped noise and multi-talker babble for English-, Chinese-, and Korean-native listeners | Zendy

Su-Hyun Jin | Zendy; Chang Liu | Zendy

Open Access

English sentence recognition in speech-shaped noise and multi-talker babble for English-, Chinese-, and Korean-native listeners

Author(s) -

Su-Hyun Jin,

Chang Liu

Publication year - 2012

Publication title -

the journal of the acoustical society of america

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.619

H-Index - 187

eISSN - 1520-8524

pISSN - 0001-4966

DOI - 10.1121/1.4757730

Subject(s) - quiet , sentence , masking (illustration) , noise (video) , speech recognition , acoustics , speech perception , linguistics , computer science , psychology , perception , natural language processing , artificial intelligence , physics , art , philosophy , image (mathematics) , quantum mechanics , neuroscience , visual arts

This study aimed to investigate English sentence recognition in quiet and two types of maskers, multi-talker babble (MTB) and long-term speech-shaped noise (LTSSN), with varied signal-to-noise ratios, for English-, Chinese-, and Korean-native listeners. Results showed that first, sentence recognition for non-native listeners was affected more by background noise than that for native listeners; second, the masking effects of LTSSN were similar between Chinese and Korean listeners, but the masking effects of MTB were greater for Chinese than for Korean listeners, suggesting possible interaction effects between the non-native listener's native language and speech-like competing noise in sentence recognition.

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