On the Impact of Language Familiarity in Talker Change Detection

Sharma, N and Krishnamohan, V and Ganapathy, S and Gangopadhayay, A and Fink, L (2020) On the Impact of Language Familiarity in Talker Change Detection. In: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, 4-8, May 2020, Barcelona, Spain, pp. 6249-6253.

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Abstract

The ability to detect talker changes when listening to conversational speech is fundamental to perception and understanding of multi-talker speech. In this paper, we propose an experimental paradigm to provide insights on the impact of language familiarity on talker change detection. Two multi-talker speech stimulus sets, one in a language familiar to the listeners (English) and the other unfamiliar (Chinese), are created. A listening test is performed in which listeners indicate the number of talkers in the presented stimuli. Analysis of human performance shows statistically significant results for: (a) lower miss (and a higher false alarm) rate in familiar versus unfamiliar language, and (b) longer response time in familiar versus unfamiliar language. These results signify a link between perception of talker attributes and language proficiency. Subsequently, a machine system is designed to perform the same task. The system makes use of the current state-of-the-art diarization approach with x-vector embeddings. A performance comparison on the same stimulus set indicates that the machine system falls short of human performance by a huge margin, for both languages.

Item Type:	Conference Paper
Publication:	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright of this article belongs to Institute of Electrical and Electronics Engineers Inc.
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	25 Aug 2020 09:43
Last Modified:	25 Aug 2020 09:43
URI:	http://eprints.iisc.ac.in/id/eprint/66383

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