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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract)

February 1, 2023

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Authors

Bhavya Ghai

Stony Brook University


Buvana Ramanan

Nokia Bell Labs


Klaus Mueller

Stony Brook University


DOI:

10.1609/aaai.v34i10.7168


Abstract:

Automatic speech recognition(ASR) systems play a key role in many commercial products including voice assistants. Typically, they require large amounts of high quality speech data for training which gives an undue advantage to large organizations which have tons of private data. We investigated if speech data obtained from publicly available sources can be further enhanced to train better speech recognition models. We begin with noisy/contaminated speech data, apply speech enhancement to produce 'cleaned' version and use both the versions to train the ASR model. We have found that using speech enhancement gives 9.5% better word error rate than training on just the original noisy data and 9% better than training on just the ground truth 'clean' data. It's performance is also comparable to the ideal case scenario when trained on noisy and it's ground truth 'clean' version.

Topics: AAAI

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HOW TO CITE:

Bhavya Ghai||Buvana Ramanan||Klaus Mueller Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract) Proceedings of the AAAI Conference on Artificial Intelligence (2020) 13793-13794.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract) AAAI 2020, 13793-13794.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller (2020). Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 13793-13794.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller. Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.13793-13794.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller. 2020. Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract). "Proceedings of the AAAI Conference on Artificial Intelligence". 13793-13794.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller. (2020) "Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract)", Proceedings of the AAAI Conference on Artificial Intelligence, p.13793-13794

Bhavya Ghai||Buvana Ramanan||Klaus Mueller, "Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract)", AAAI, p.13793-13794, 2020.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller. "Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.13793-13794.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller. "Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 13793-13794.

Bhavya Ghai||Buvana Ramanan||Klaus Mueller. Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract). AAAI[Internet]. 2020[cited 2023]; 13793-13794.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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