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A Hybrid Approach for Speaker Tracking Based on TDOA and Data-Driven Models

  • Published:2018-04 Issue:4 Volume:26 Page:725-735
  • 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:

Laufer-Goldshtein Bracha,Talmon RonenORCID,Gannot SharonORCID

Funder

State of Lower Saxony

Adams Foundation of the Israel Academy of Sciences and Humanities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Cited by 24 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Latent-KalmanNet: Learned Kalman Filtering for Tracking From High-Dimensional Signals;IEEE Transactions on Signal Processing;2024

2. Closed-form multiple source direction-of-arrival estimator under reverberant environments;The Journal of the Acoustical Society of America;2023-10-01

3. Learned Kalman Filtering in Latent Space with High-Dimensional Data;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

4. Joint short-time speaker recognition and tracking using sparsity-based source detection;Acta Acustica;2023

5. Training-Based Multiple Source Tracking Using Manifold-Learning and Recursive Expectation-Maximization;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2023
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