Title :
HRTF-based localization and separation of multiple sound sources
Author :
Rothbucher, Martin ; Durkovic, Marko ; Habigt, Tim ; Shen, Hao ; Diepold, Klaus
Author_Institution :
Inst. for Data Process., Tech. Univ. Munchen, Mϋnchen, Germany
Abstract :
The human auditory system excels at pinpointing and distinguishing multiple sound sources in noisy and reverberant environments. Mobile robotic platforms implement such capabilities with varying success, classically solving localization and separation independently. This paper presents an algorithm utilizing Head-Related Transfer Function (HRTF) based localization to aid the task of separation. HRTFs for robotic binaural hearing represent the digital emulation of a human´s innate direction-dependent filtering for solving the localization problem in a compact and robust manner. The overall result of the presented algorithm for robotic binaural hearing is an HRTF-based localization and separation system, capable of dynamically and intelligently processing simultaneously active sound sources.
Keywords :
acoustic generators; acoustic signal processing; blind source separation; hearing; mobile robots; reverberation; transfer functions; HRTF-based sound source localization; HRTF-based sound source separation; active sound sources; head-related transfer function; human auditory system; human innate direction-dependent filtering digital emulation; mobile robotic platforms; noisy environments; reverberant capabilities; robotic binaural hearing; Auditory system; Correlation; Humans; Indexes; Microphones; Robots; Source separation;
Conference_Titel :
RO-MAN, 2012 IEEE
Conference_Location :
Paris
Print_ISBN :
978-1-4673-4604-7
Electronic_ISBN :
1944-9445
DOI :
10.1109/ROMAN.2012.6343894