Binaural lateral localization of multiple sources in real environments using a kurtosis-driven split-EM algorithm
| Autor: | J. M. Pérez-Lorenzo, F. Rivas, Raquel Viciana-Abad, P. Reche-Lopez |
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| Rok vydání: | 2018 |
| Předmět: |
Echoic memory
business.industry Computer science Process (computing) Direction of arrival 020206 networking & telecommunications Context (language use) Pattern recognition 02 engineering and technology 01 natural sciences Artificial Intelligence Control and Systems Engineering 0103 physical sciences Expectation–maximization algorithm 0202 electrical engineering electronic engineering information engineering Kurtosis Artificial intelligence Electrical and Electronic Engineering business 010301 acoustics Binaural recording |
| Zdroj: | Engineering Applications of Artificial Intelligence. 69:137-146 |
| ISSN: | 0952-1976 |
| Popis: | In this work a method for an unsupervised lateral localization of simultaneous sound sources is presented. Following a binaural approach, the kurtosis-driven split-EM algorithm (KDS-EM) implemented is able to estimate the direction of arrival of relevant sound sources without knowing a priori their number. Information about the localization is integrated within a period of observation time to serve as an auditory memory in the context of social robotics. Experiments have been conducted using two types of observation times, one shorter with the purpose of analyzing its performance in a reactive level, and other longer that allows the analysis of its contribution as an input of the building process of the sorroundings auditory models that servesto drive a more deliberative behavior. The system has been tested in real and reverberant environments, achieving a good performance based on an over-modeling process that is able to isolate the location of the relevant sources from adverse acoustic effects, such as reverberations. |
| Databáze: | OpenAIRE |
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