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  • SPS
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    Length: 12:03
04 May 2020

High intelligibility can be achieved when listening to synthetic or artificially-produced speech under adverse conditions. But can listener preferences reveal any extra information when intelligibility is at ceiling? This paper describes a real-time speech modification technique which allows evaluation of the impact of individual speech properties on listeners' preferences. The current study investigates spectral tilt, a feature which also changes naturally in different speaking styles such as Lombard speech. In the listening experiment, participants were asked to adjust the spectral tilt in masked conditions; subsequently, intelligibility was assessed. Listeners preferred flatter spectral tilts as SNR decreased. Additionally, tilt preferences were evident even while intelligibility was at or close to ceiling levels, suggesting that preferences provide information over and above that measured in traditional intelligibility-based studies. On the basis of these findings a method for probabilistic modelling of listener preferences, useful in the development of speech enrichment algorithms, is proposed.

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