Learning Multi-Dimensional Speaker Localization: Axis Partitioning, Unbiased Label Distribution, and Data Augmentation-Reference-Cited by-同舟云学术

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Learning Multi-Dimensional Speaker Localization: Axis Partitioning, Unbiased Label Distribution, and Data Augmentation

Published:2024 Issue: Volume:32 Page:4013-4025
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:

Feng Linfeng¹^ORCID,Gong Yijun²,Liu Zhi³^ORCID,Zhang Xiao-Lei¹^ORCID,Li Xuelong⁴^ORCID

Affiliation:

1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, China

2. Xi'an Research Institute of Navigation Technology (CETC20), Xi'an, China

3. Shenzhen Huangli Techonogies Company Ltd., Shenzhen, China

4. Institute of Artificial Intelligence (TeleAI), China Telecom Corporation Ltd., Beijing, China

Funder

National Science Foundation of China

Project of the Science, Technology

Innovation Commission of Shenzhen Municipality, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6570655/10304349/10609831.pdf?arnumber=10609831

Reference48 articles.

1. A survey of sound source localization with deep learning methods

2. Directional ASR: A New Paradigm for E2E Multi-Speaker Speech Recognition with Source Localization

3. Localization based Sequential Grouping for Continuous Speech Separation

4. L-SpEx: Localized Target Speaker Extraction

5. Multi-Channel Conversational Speaker Separation via Neural Diarization

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