Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise

Spectral weights in octave-frequency bands from 0.25 to 4 kHz were estimated for speech-in-noise recognition using two sentence materials (i.e., the IEEE and AzBio sentences). The masking noise was either unmodulated or sinusoidally amplitude-modulated at 8 Hz. The estimated spectral weights did not...

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Detalles Bibliográficos
Autores principales: Shen, Yi, Langley, Lauren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Acoustical Society of America 2023
Materias:
Speech Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155216/
https://www.ncbi.nlm.nih.gov/pubmed/37125871
http://dx.doi.org/10.1121/10.0017934
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author Shen, Yi
Langley, Lauren
author_facet Shen, Yi
Langley, Lauren
author_sort Shen, Yi
collection PubMed
description Spectral weights in octave-frequency bands from 0.25 to 4 kHz were estimated for speech-in-noise recognition using two sentence materials (i.e., the IEEE and AzBio sentences). The masking noise was either unmodulated or sinusoidally amplitude-modulated at 8 Hz. The estimated spectral weights did not vary significantly across two test sessions and were similar for the two sentence materials. Amplitude-modulating the masker increased the weight at 2 kHz and decreased the weight at 0.25 kHz, which may support an upward shift in spectral weights for temporally fluctuating maskers.
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spelling pubmed-101552162023-05-04 Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise Shen, Yi Langley, Lauren JASA Express Lett Speech Communication Spectral weights in octave-frequency bands from 0.25 to 4 kHz were estimated for speech-in-noise recognition using two sentence materials (i.e., the IEEE and AzBio sentences). The masking noise was either unmodulated or sinusoidally amplitude-modulated at 8 Hz. The estimated spectral weights did not vary significantly across two test sessions and were similar for the two sentence materials. Amplitude-modulating the masker increased the weight at 2 kHz and decreased the weight at 0.25 kHz, which may support an upward shift in spectral weights for temporally fluctuating maskers. Acoustical Society of America 2023-05 2023-05-01 /pmc/articles/PMC10155216/ /pubmed/37125871 http://dx.doi.org/10.1121/10.0017934 Text en © 2023 Author(s). 2691-1191/2023/3(5)/055202/9 https://creativecommons.org/licenses/by/4.0/All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Speech Communication
Shen, Yi
Langley, Lauren
Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise
title Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise
title_full Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise
title_fullStr Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise
title_full_unstemmed Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise
title_short Spectral weighting for sentence recognition in steady-state and amplitude-modulated noise
title_sort spectral weighting for sentence recognition in steady-state and amplitude-modulated noise
topic Speech Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155216/
https://www.ncbi.nlm.nih.gov/pubmed/37125871
http://dx.doi.org/10.1121/10.0017934
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AT langleylauren spectralweightingforsentencerecognitioninsteadystateandamplitudemodulatednoise

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