A new hierarchical binaural sound source localization method based on Interaural Matching Filter

Binaural sound source localization is an important technique in friendly Human-Robot Interaction (HRI) for its easy-implementation with only two microphones. This paper develops a robust method based on a hierarchical probabilistic model. Reliable frequency sub-bands are used to PHAT - ργ method in the first layer to obtain a priori crude Interaural Time-Delay (ITD) and the probabilistic distribution of candidate azimuths. The second layer utilizes Interaural Intensity Difference (IID) to reduce matching time and refine candidate azimuths as well as elevations. A novel feature named Interaural Matching Filter (IMF), which can eliminate the difference between ITDs and IIDs, is proposed in the third layer. The probability of sound source location is acquired by computing the similarity between the IMF of received binaural signal and the IMFs in templates. Finally, combined with the former ITDs and IIDs, the similarity matrix is used to make a decision of sound source location based on a Bayes rule. Our innovation lies in adding selecting reliable frequency components into time-delay estimation and foremost taking IMF as a feature of sound source. Compared with several state-of-the-art algorithms, experimental results show our approach has a better performance even in noisy environments without increasing storages, and also has less time complexity.