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Creating speech zones with self-distributing acoustic swarms
Malek Itani1, Tuochao Chen2, Takuya Yoshioka3
1Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA. malek@cs.washington.edu.
Nature Communications
|September 22, 2023
Summary
Introducing an acoustic swarm, a novel system for sound localization. This technology uses a self-distributing microphone array and neural networks to separate and pinpoint multiple speakers in real-time, creating defined speech zones.
Area of Science:
- Acoustic signal processing
- Robotics
- Machine learning
Background:
- Separating concurrent speech and pinpointing sound sources in 2D space is a complex challenge.
- Existing methods often rely on cameras or fixed infrastructure, limiting flexibility.
Purpose of the Study:
- To develop the first acoustic swarm for centimeter-resolution sound localization and speech separation.
- To enable precise 2D spatial awareness of multiple concurrent speakers without external hardware.
Main Methods:
- Formation of a self-distributing wireless microphone array (acoustic swarm).
- Utilizing an attention-based neural network framework for speech separation and localization.
- Real-world testing in reverberant environments.
Main Results:
- Successful localization and separation of 3-5 concurrent speech sources.
- Median and 90-percentile 2D localization errors of 15 cm and 50 cm, respectively.
- Demonstrated centimeter-resolution cooperative navigation using sound.
Conclusions:
- The acoustic swarm offers a camera-free solution for separating and localizing multiple speakers.
- Enables novel applications such as mute zones, active zones, and location-aware interactions.
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