Assessing the Impact of Noise and Speech Enhancement on the Intelligibility of Speech Codecs

Fuente: arXiv
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Autori principali: Behringer, Lyonel, Leschanowsky, Anna, Rajasekhar, Anjana, Kratsch, Emily, Fuchs, Guillaume
Natura: Preprint
Pubblicazione: 2026
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author Behringer, Lyonel
Leschanowsky, Anna
Rajasekhar, Anjana
Kratsch, Emily
Fuchs, Guillaume
author_facet Behringer, Lyonel
Leschanowsky, Anna
Rajasekhar, Anjana
Kratsch, Emily
Fuchs, Guillaume
contents Preserving speech intelligibility is a minimum requirement for speech codecs in communication. Recently, very low-bitrate neural codecs have gained interest for replacing classical codecs, reinforcing the need to evaluate whether intelligibility is preserved in realistic scenarios. In this paper, we evaluate the intelligibility and listening effort of classical and neural speech codecs in clean and noisy conditions. Further, we assess the impact of speech enhancement (SE) before coding, simulating a possible audio processing pipeline. The results show that classical codecs are more noise robust than neural codecs. Further, SE can lead to significant intelligibility and listening effort improvements for codecs otherwise negatively affected by noise. Listening effort reveals nuanced differences when intelligibility is saturated. Lastly, objective intelligibility based on automatic speech recognition is highly correlated with subjective intelligibility scores averaged per condition.
format Preprint
id arxiv_https___arxiv_org_abs_2605_03776
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Assessing the Impact of Noise and Speech Enhancement on the Intelligibility of Speech Codecs
Behringer, Lyonel
Leschanowsky, Anna
Rajasekhar, Anjana
Kratsch, Emily
Fuchs, Guillaume
Audio and Speech Processing
Preserving speech intelligibility is a minimum requirement for speech codecs in communication. Recently, very low-bitrate neural codecs have gained interest for replacing classical codecs, reinforcing the need to evaluate whether intelligibility is preserved in realistic scenarios. In this paper, we evaluate the intelligibility and listening effort of classical and neural speech codecs in clean and noisy conditions. Further, we assess the impact of speech enhancement (SE) before coding, simulating a possible audio processing pipeline. The results show that classical codecs are more noise robust than neural codecs. Further, SE can lead to significant intelligibility and listening effort improvements for codecs otherwise negatively affected by noise. Listening effort reveals nuanced differences when intelligibility is saturated. Lastly, objective intelligibility based on automatic speech recognition is highly correlated with subjective intelligibility scores averaged per condition.
title Assessing the Impact of Noise and Speech Enhancement on the Intelligibility of Speech Codecs
topic Audio and Speech Processing
url https://arxiv.org/abs/2605.03776