A glimpsing model of speech perception in noise
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Abstract
Do listeners process noisy speech by taking advantage of "glimpses"-spectrotemporal regions in which the target signal is least affected by the background? This study used an automatic speech recognition system, adapted for use with partially specified inputs, to identify consonants in noise. Twelve masking conditions were chosen to create a range of glimpse sizes. Several different glimpsing models were employed, differing in the local signal-to-noise ratio (SNR) used for detection, the minimum glimpse size, and the use of information in the masked regions. Recognition results were compared with behavioral data. A quantitative analysis demonstrated that the proportion of the time-frequency plane glimpsed is a…
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Topics
Keywords
- Speech recognition
- Computer science
- Voice
- Intelligibility (philosophy)
- Speech perception
- Perception
- Consonant
- Acoustics
UN Sustainable Development Goals
- Quality Education
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