A Deep Learning Speech Enhancement Architecture Optimised for Speech Recognition and Hearing Aids
Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N. 2023. A Deep Learning Speech Enhancement Architecture Optimised for Speech Recognition and Hearing Aids. The 35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). Atlanta, Georgia (USA) 06 - 08 Nov 2023 IEEE Computer Society. https://doi.org/10.1109/ICTAI59109.2023.00088
|Nossier, S. A., Wall, J., Moniri, M., Glackin, C. and Cannings, N.
With the fast progression of the speech enhancement field after the introduction of deep learning techniques, there is a need to consider the adjustments needed to employ these techniques for real-life applications. In this work, we present an optimised deep learning speech enhancement architecture for automatic speech recognition and hearing aids, two key speech enhancement applications. A speech enhancement architecture with a signal-to-noise ratio switch is presented for automatic speech recognition systems, to avoid denoising artifacts that cause performance degradation in the case of clean or high signal-tonoise speech. Moreover, a smart speech enhancement architecture is presented for hearing aids to retain important emergency noise in the audio signal. The presented work achieved 13.9% reduction in the word error rate of an automatic speech recognition system. Additionally, the smart speech enhancement architecture resulted in 0.18 improvement in HAAQI audio quality metric.
|Automatic speech recognition; convolutional classifiers; deep learning; hearing aids; speech enhancement
|The 35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
|IEEE Computer Society
|Accepted author manuscript
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|Publication process dates
|04 Sep 2023
|18 Sep 2023
|2023 IEEE 35th International Conference on Tools with Artificial Intelligence Proceedings
|Digital Object Identifier (DOI)
|Web address (URL) of conference proceedings
|© 2023, IEEE.
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