Abstract
This work addresses the problem of automatic speaker localization and tracking in a real lecture scenario. Evaluation criteria recently adopted under CHIL and NIST benchmarking are outlined. Two speaker localization systems are described, which are based on the use of Generalized Cross Correlation Phase Transform analysis and Global Coherence Field. Benchmarking results, obtained on a set of 13 lectures, showed an average RMS error of about 30 cm in the speaker localization.
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Omologo, M., Svaizer, P., Brutti, A., Cristoforetti, L. (2006). Speaker Localization in CHIL Lectures: Evaluation Criteria and Results. In: Renals, S., Bengio, S. (eds) Machine Learning for Multimodal Interaction. MLMI 2005. Lecture Notes in Computer Science, vol 3869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11677482_40
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DOI: https://doi.org/10.1007/11677482_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32549-9
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