PMMSD: Development of the Matrix Sentence Intelligibility Dataset for Mandarin with Lombard Effect
- Resource Type
- Conference
- Authors
- Pei, Hanchen; Yang, Yuhong; Chen, Xufeng; Liu, Qingmu; Chen, Hongyang; Tu, Weiping; Lin, Song
- Source
- ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2023 - 2023 IEEE International Conference on. :1-5 Jun, 2023
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Buildings
Interference
Signal processing
Acoustics
Speech processing
Matrix sentences
Lombard effect
intelligibility
SRT test
- Language
- ISSN
- 2379-190X
This paper presents a Paired Mandarin Matrix Sentence Dataset (PMMSD), which will be available after publication. PMMSD is the first Mandarin matrix sentence intelligibility dataset containing both plain and Lombard speech for scientific research. The results verify that different Lombard styles would affect word intelligibility to different degrees and the Lombard effect helps maintain homogeneous intelligibility against contextual interference. All of the discoveries indicate that the Lombard effect should be considered when building intelligibility datasets with noise in the future.