Estimating speaker direction on a humanoid robot with binaural acoustic signals

TL;DR

This paper introduces an optimized binaural sound source localization method for humanoid robots to accurately estimate human talker direction in real-time interactions, validated with real data and latency analysis.

Contribution

It presents a novel parameter optimization approach for DOA estimation tailored for humanoid robots, enhancing real-time speech interaction capabilities.

Findings

Optimized DOA parameters improve localization accuracy.

Bayesian optimization outperforms brute force methods.

Latency considerations are addressed for real-time deployment.

Abstract

To achieve human-like behaviour during speech interactions, it is necessary for a humanoid robot to estimate the location of a human talker. Here, we present a method to optimize the parameters used for the direction of arrival (DOA) estimation, while also considering real-time applications for human-robot interaction scenarios. This method is applied to binaural sound source localization framework on a humanoid robotic head. Real data is collected and annotated for this work. Optimizations are performed via a brute force method and a Bayesian model based method, results are validated and discussed, and effects on latency for real-time use are also explored.