Leveraging Confidence Models for Identifying Challenging Data Subgroups in Speech Models-Reference-Cited by-同舟云学术

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Leveraging Confidence Models for Identifying Challenging Data Subgroups in Speech Models

Published:2024-04-14 Issue: Volume:33 Page:134-138
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Container-title:2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
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Author:

Koudounas Alkis¹,Pastor Eliana¹,Mazzia Vittorio²,Giollo Manuel²,Gueudre Thomas²,Reale Elisa²,Attanasio Giuseppe³,Cagliero Luca¹,Cumani Sandro¹,De Alfaro Luca⁴,Baralis Elena¹,Amberti Daniele²

Affiliation:

1. Politecnico di Torino,Turin,Italy

2. Amazon,Alexa AI,Turin,Italy

3. Bocconi University,Milan,Italy

4. University of California,Santa Cruz,CA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10625769/10625780/10626001.pdf?arnumber=10626001

Reference17 articles.

1. Improving Fairness and Robustness in End-to-End Speech Recognition Through Unsupervised Clustering

2. Speaker clustering and transformation for speaker adaptation in large-vocabulary speech recognition systems

3. Integration of speaker and speech recognition systems

4. Exploring Subgroup Performance in End-to-End Speech Models

5. Librispeech: An ASR corpus based on public domain audio books

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