Towards Comprehensive Subgroup Performance Analysis in Speech Models-Reference-Cited by-同舟云学术

Towards Comprehensive Subgroup Performance Analysis in Speech Models

Published:2024 Issue: Volume:32 Page:1468-1480
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Koudounas Alkis¹^ORCID,Pastor Eliana¹^ORCID,Attanasio Giuseppe²^ORCID,Mazzia Vittorio³^ORCID,Giollo Manuel³^ORCID,Gueudre Thomas³^ORCID,Reale Elisa³^ORCID,Cagliero Luca¹^ORCID,Cumani Sandro¹^ORCID,de Alfaro Luca⁴^ORCID,Baralis Elena¹^ORCID,Amberti Daniele³^ORCID

Affiliation:

1. Politecnico di Torino, Turin, Italy

2. MilaNLP Group and the Data and Marketing Insights Unit, Bocconi Institute for Data Science and Analysis, Milan, Italy

3. AGI, Amazon, Turin, Italy

4. University of California, Santa Cruz, CA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570655/10304349/10430478.pdf?arnumber=10430478

Reference41 articles.

1. An overview of end-to-end language understanding and dialog management for personal digital assistants

2. A Survey on Chatbot Implementation in Customer Service Industry through Deep Neural Networks

3. Speech Technology for Healthcare: Opportunities, Challenges, and State of the Art

4. Towards Paralinguistic-Only Speech Representations for End-to-End Speech Emotion Recognition

5. Voice recognition still has significant race and gender biases;Bajorek;Harvard Bus. Rev.,2019

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1. Houston we have a Divergence: A Subgroup Performance Analysis of ASR Models;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

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