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

Audibility emphasis of low-level sounds improves consonant identification while preserving vowel identification for cochlear implant users.
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DOI:
10.1016/j.specom.2022.01.001
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发表时间:
2022-03
影响因子:
3.2
通讯作者:
Swaminathan, Jayaganesh
Swaminathan, Jayaganesh
中科院分区:
计算机科学3区
文献类型:
--
作者:
Goldsworthy, Raymond L.;Bissmeyer, Susan R. S.;Swaminathan, Jayaganesh

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对于听力损失的听者来说,辅音感知是一项挑战,而通过通信渠道传输语音会进一步恶化辅音的声学效果。部分挑战来自辅音的短期低能量光谱-时间分布(例如,相对于元音)。我们假设一种可听性增强方法,旨在提高低音的能量,可以在不降低元音识别的情况下提高辅音的识别。我们对11名人工耳蜗使用者进行了这一假设的测试,他们使用媒体设备和人工耳蜗设置完成了远程在线听力实验,他们在进行视频通话时最常用的设置。测量纯音刺激的响度增长和检测阈值,以表征测试条件的相对响度。辅音和元音识别是在安静和语音形状的噪音中测量的,信噪比逐渐困难(+12,+6,0,- 6 dB信噪比)。在这些条件下,分别使用和不使用可听性强调算法进行测试,该算法旨在增强声源处的辅音识别。结果表明,该算法在不影响元音识别的情况下,提高了人工耳蜗用户在噪声中的辅音识别能力。我们得出的结论是,在视频通话或其他电信通信的情况下,低水平的音频强调可以提高人工耳蜗用户的语音识别,目标语音可以与环境噪声分开预处理。
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.
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