Print Email Facebook Twitter Binaural Sound Localization Based on Reverberation Weighting and Generalized Parametric Mapping Title Binaural Sound Localization Based on Reverberation Weighting and Generalized Parametric Mapping Author Pang, Cheng (Peking University) Liu, Hong (Peking University) Zhang, J. (TU Delft Signal Processing Systems) Li, Xiaofei (Inria Grenoble Rhône-Alpes) Date 2017 Abstract Binaural sound source localization is an important technique for speech enhancement, video conferencing, and human-robot interaction, etc. However, in realistic scenarios, the reverberation and environmental noise would degrade the precision of sound direction estimation. Therefore, reliable sound localization is essential to practical applications. To deal with these disturbances, this paper presents a novel binaural sound source localization approach based on reverberation weighting and generalized parametric mapping. First, the reverberation weighting as a preprocessing stage, is used to separately suppress the early and late reverberation, while preserving interaural cues. Then, two binaural cues, i.e., interaural time and intensity differences, are extracted from the frequency-domain representations of dereverberated binaural signals for the online localization. Their corresponding templates are established using the training data. Furthermore, the generalized parametric mapping is proposed to build a generalized parametric model for describing relationships between azimuth and binaural cues analytically. Finally, a two-step sound localization process is introduced to refine azimuth estimation based on the generalized parametric model and template matching. Experiments in both simulated and real scenarios validate that the proposed method can achieve better localization performance compared to state-of-the-art methods. Subject Binaural localizationreverberation weightinggeneralized parametric mappingtemplate matching To reference this document use: http://resolver.tudelft.nl/uuid:cd5e4f56-a96a-4758-b84b-1698e3fa931d DOI https://doi.org/10.1109/TASLP.2017.2703650 ISSN 2329-9290 Source IEEE - ACM Transactions on Audio, Speech, and Language Processing, 25 (8), 1618-1632 Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type journal article Rights © 2017 Cheng Pang, Hong Liu, J. Zhang, Xiaofei Li Files PDF 26021770_Pangc_aslptrans.pdf 2.08 MB Close viewer /islandora/object/uuid:cd5e4f56-a96a-4758-b84b-1698e3fa931d/datastream/OBJ/view