Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
167 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Study of speaker localization under dynamic and reverberant environments (2311.16927v1)

Published 28 Nov 2023 in eess.AS

Abstract: Speaker localization in a reverberant environment is a fundamental problem in audio signal processing. Many solutions have been developed to tackle this problem. However, previous algorithms typically assume a stationary environment in which both the microphone array and the sound sources are not moving. With the emergence of wearable microphone arrays, acoustic scenes have become dynamic with moving sources and arrays. This calls for algorithms that perform well in dynamic environments. In this article, we study the performance of a speaker localization algorithm in such an environment. The study is based on the recently published EasyCom speech dataset recorded in reverberant and noisy environments using a wearable array on glasses. Although the localization algorithm performs well in static environments, its performance degraded substantially when used on the EasyCom dataset. The paper presents performance analysis and proposes methods for improvement.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (12)
  1. The importance of time-frequency averaging for binaural speaker localization in reverberant environments. In INTERSPEECH, pages 5071–5075, 2020.
  2. M. Brandstein and D. Ward. Microphone arrays: signal processing techniques and applications. Springer Science & Business Media, 2001.
  3. A robust method for speech signal time-delay estimation in reverberant rooms. In 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, volume 1, pages 375–378. IEEE, 1997.
  4. Easycom: An augmented reality dataset to support algorithms for easy communication in noisy environments. 2021.
  5. C. Evers and P. A. Naylor. Acoustic slam. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26(9):1484–1498, 2018.
  6. The locata challenge data corpus for acoustic source localization and tracking. In 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM), pages 410–414. IEEE, 2018.
  7. L. Madmoni and B. Rafaely. Improved direct-path dominance test for speaker localization in reverberant environments. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 2424–2428. IEEE, 2018.
  8. The perceptual significance of high-frequency energy in the human voice. Frontiers in Psychology, 5:587, 2014.
  9. R. Schmidt. Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas and Propagation, 34(3):276–280, 1986.
  10. Space domain-based selection of direct-sound bins in the context of improved robustness to reverberation in direction of arrival estimation. In Proc. 11th European Congress and Exposition on Noise Control Engineering (EURONOISE18), pages 2589–2596, 2018.
  11. Beamforming: A versatile approach to spatial filtering. IEEE ASSP Magazine, 5(2):4–24, 1988.
  12. W. Wang and R. Wu. High-dynamic doa estimation based on weighted l 1 minimization. Progress In Electromagnetics Research C, 42:253–265, 2013.
Citations (2)

Summary

We haven't generated a summary for this paper yet.