EEG-based Objective Quality Assessment of Interrupted Speech

Shangdi Liao; Zhixing Liu; Fei Chen

10.1109/EMBC40787.2023.10340901

2023

45th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

2375-7477

1558-4615

979-8-3503-2448-8

2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

1-4

24-27 July 2023

Sydney, Australia

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

As an important dimension of speech degradation, interruption destroys the acoustic waveform information of a speech signal and seriously affects the quality rating in speech perception. Existing studies assessing the quality of interrupted speech mainly focus on subjective methods. This work used event-related potentials (ERPs) to objectively investigate the effects of two interruption factors (i.e., interruption duty cycle and interruption rate) on the perceived quality of the periodically interrupted speech. An oddball-paradigm based ERP experiment was designed, and the periodically interrupted stimuli were presented to participants in the ERP experiment. Meanwhile, participants were instructed to provide their subjective quality ratings of interrupted speech under the same interruption conditions. The experimental results showed that the degree of both interruption duty cycle and interruption rate affected the peak latency of mismatch negativity (MMN) of the collected ERP response, with a smaller MMN peak latency under conditions with a smaller interruption duty cycle or a larger interruption rate. These findings are largely consistent with the subjective quality rating results, suggesting that the peak latency of MMN response can be potentially used as an objective quality indicator of the periodically interrupted speech.

speech quality objective evaluation interrupted speech event-related potential (ERP) mismatch negativity (MMN)

第一

英语

EI ; CPCI-S

Shenzhen Key Laboratory of Robotics Perception and Intelligence[ZDSYS20200810171800001]

Computer Science ; Engineering

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical

WOS:001133788304016

20240215361428

IEEE

Department of Electrical and Electronic Engineering, Shenzhen Key Laboratory of Robotics Perception and Intelligence, Southern University of Science and Technology, Shenzhen, China

Shangdi Liao,Zhixing Liu,Fei Chen. EEG-based Objective Quality Assessment of Interrupted Speech[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1-4.