Is audio signal processing still useful in the era of machine learning?

Emmanuel Vincent 1
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Audio signal processing has long been the obvious approach to problems such as microphone array processing, active noise control, or speech enhancement. Yet, it is increasingly being challenged by black-box machine learning approaches based on, e.g., deep neural networks (DNN), which have already achieved superior results on certain tasks. In this talk, I will try to convince that machine learning approaches shouldn’t be disregarded, but that black boxes won’t solve these problems either. There is hence an opportunity for signal processing researchers to join forces with machine learning researchers and solve these problems together. I will provide examples of this multi-disciplinary approach for audio source separation and robust automatic speech recognition.
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2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). 2015
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https://hal.inria.fr/hal-01183506
Contributeur : Emmanuel Vincent <>
Soumis le : samedi 8 août 2015 - 23:44:58
Dernière modification le : jeudi 11 janvier 2018 - 06:27:31

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  • HAL Id : hal-01183506, version 1

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Emmanuel Vincent. Is audio signal processing still useful in the era of machine learning?. 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). 2015. 〈hal-01183506〉

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