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The MBSTOI Binaural Intelligibility Metric Using a Close-Talking Microphone Reference

Pierre Guiraud (Imperial College London); Alastair H Moore (Imperial College London); Rebecca Vos (Imperial College London); Patrick A. Naylor (Imperial College London); Mike Brookes (Imperial College London)

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06 Jun 2023

Intelligibility metrics are a fast way to determine how comprehensible a target signal is in a noisy situation. Most metrics however rely on having a clean reference signal for computation and are not adapted to live recordings. In this paper the deep correlation modified binaural short time objective intelligibility metric (Dcor-MBSTOI) is evaluated with a single-channel close-talking microphone signal as the reference. This reference signal inevitably contains some background noise and crosstalk from non-target sources. It is found that intelligibility is overestimated when using the close-talking microphone signal directly but that this overestimation can be eliminated by applying speech enhancement to the reference signal.

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