Simple spectral subtraction method enhances speech intelligibility in noise for cochlear implant listeners
It has been demonstrated that while clean speech is well intelligible by most cochlear implant (CI) listeners, noise quickly degrades speech intelligibility. To remedy the situation, CI manufacturers integrate noise reduction (NR) algorithms (often using multiple microphones) in their CI processors, and they report that CI users benefit from this measure. We have implemented a single-microphone NR scheme based on spectral subtraction with minimum statistics to see if such a simple algorithm can also effectively increase speech intelligibility in noise. We measured speech reception thresholds using both speech-shaped and car noise in 5 CI users and 23 normal-hearing listeners. For the latter group, CI hearing was acoustically simulated. In case of the CI users, the performance of the proposed NR algorithm was also compared to that of the CI processor’s built-in one. Our NR algorithm enhances intelligibility greatly in combination with the acoustic simulation regardless of the noise type; these effects are highly significant. For the CI users, trends agree with the above finding (for both the proposed and the built-in NR algorithms), however, due to low sample number, these differences did not reach statistical significance. We conclude that simple spectral subtraction can enhance speech intelligibility in noise for CI listeners and may even keep up with proprietary NR algorithms.
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