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Lombard Effect for Bilingual Speakers in Cantonese and English: importance of spectro-temporal features ...
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Abstract:
For a better understanding of the mechanisms underlying speech perception and the contribution of different signal features, computational models of speech recognition have a long tradition in hearing research. Due to the diverse range of situations in which speech needs to be recognized, these models need to be generalizable across many acoustic conditions, speakers, and languages. This contribution examines the importance of different features for speech recognition predictions of plain and Lombard speech for English in comparison to Cantonese in stationary and modulated noise. While Cantonese is a tonal language that encodes information in spectro-temporal features, the Lombard effect is known to be associated with spectral changes in the speech signal. These contrasting properties of tonal languages and the Lombard effect form an interesting basis for the assessment of speech recognition models. Here, an automatic speech recognition-based ASR model using spectral or spectro-temporal features is evaluated ... : Submitted to INTERSPEECH2022 ...
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Keyword:
Audio and Speech Processing eess.AS; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD
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URL: https://dx.doi.org/10.48550/arxiv.2204.06907 https://arxiv.org/abs/2204.06907
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Age-Related Differences in Lexical Access Relate to Speech Recognition in Noise
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Age-related differences in lexical access relate to speech recognition in noise
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Influence of vocabulary knowledge & lexical access times on speech intelligibility in different acoustic conditions
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