ArticleThe Journal of the Acoustical Society of America2022
The effects of Lombard perturbation on speech intelligibility in noise for normal hearing and cochlear implant listeners.
Article in The Journal of the Acoustical Society of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 6 citations in OpenAlex.
- Music Therapy Intervention in an Open Bay Neonatal Intensive Care Unit Room Is Associated with Less Noise and Higher Signal to Noise Ratios: A Case-Control Study.Children (Basel, Switzerland) · 2022Article
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2 authors at 1 institution in 1 country.
Funding
Abstract
Natural compensation of speech production in challenging listening environments is referred to as the Lombard effect (LE). The resulting acoustic differences between neutral and Lombard speech have been shown to provide intelligibility benefits for normal hearing (NH) and cochlear implant (CI) listeners alike. Motivated by this outcome, three LE perturbation approaches consisting of pitch, duration, formant, intensity, and spectral contour modifications were designed specifically for CI listeners to combat speech-in-noise performance deficits. Experiment 1 analyzed the effects of loudness, quality, and distortion of approaches on speech intelligibility with and without formant-shifting. Significant improvements of +9.4% were observed in CI listeners without the formant-shifting approach at +5 dB signal-to-noise ratio (SNR) large-crowd-noise (LCN) when loudness was controlled, however, performance was found to be significantly lower for NH listeners. Experiment 2 evaluated the non-formant-shifting approach with additional spectral contour and high pass filtering to reduce spectral smearing and decrease distortion observed in Experiment 1. This resulted in significant intelligibility benefits of +30.2% for NH and +21.2% for CI listeners at 0 and +5 dB SNR LCN, respectively. These results suggest that LE perturbation may be useful as front-end speech modification approaches to improve intelligibility for CI users in noise.
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