Audibility emphasis of low-level sounds improves consonant identification while preserving vowel identification for cochlear implant users

• Published in: Speech communication Vol. 137; pp. 52 - 59
• Main Authors: Goldsworthy, Raymond L., Bissmeyer, Susan R.S., Swaminathan, Jayaganesh
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.02.2022; Elsevier Science Ltd
• Subjects: Acoustics; Algorithms; Background noise; Cochlear implants; compression; consonant enhancement; Consonants; Consonants (speech); Hearing disorders; Identification; Loudness; Noise; Signal to noise ratio; Sound identification; Sound intensity; Speech comprehension; Speech perception; Speech recognition; Video teleconferencing; Vowel perception; Vowels; Speech comprehension; consonant enhancement; compression; cochlear implants
• ISSN: 0167-6393; 1872-7182
• DOI: 10.1016/j.specom.2022.01.001

•Audibility emphasis of low-level sounds improves consonant identification in noise for cochlear implant users without affecting vowel identification.•Audibility emphasis can be used to improve consonant identification for cochlear implant users for telecommunications scenarios such as video calls for which the target speech can be separately processed from the background noise. Consonant perception is challenging for listeners with hearing loss, and transmission of speech over communication channels further deteriorates the acoustics of consonants. Part of the challenge arises from the short-term low energy spectro-temporal profile of consonants (for example, relative to vowels). We hypothesized that an audibility enhancement approach aimed at boosting the energy of low-level sounds would improve identification of consonants without diminishing vowel identification. We tested this hypothesis with 11 cochlear implant users, who completed an online listening experiment remotely using the media device and implant settings that they most commonly use when making video calls. Loudness growth and detection thresholds were measured for pure tone stimuli to characterize the relative loudness of test conditions. Consonant and vowel identification were measured in quiet and in speech-shaped noise for progressively difficult signal-to-noise ratios (+12, +6, 0, -6 dB SNR). These conditions were tested with and without an audibility-emphasis algorithm designed to enhance consonant identification at the source. The results show that the algorithm improves consonant identification in noise for cochlear implant users without diminishing vowel identification. We conclude that low-level emphasis of audio can improve speech recognition for cochlear implant users in the case of video calls or other telecommunications where the target speech can be preprocessed separately from environmental noise.