Abstract
This paper presents a speaker localization system, which is an entry to Rich Transcription 2005 Spring Meeting Recognition Evaluation. The system is developed in the Institute of Signal Processing at Tampere University of Technology (TUT). The paper describes the framework of the evaluation and the proposed localization system. This paper is an extension to [1] giving the actual performance values of the system.
The localization system is based on spatially separate sensor stations. The sensor stations estimate Direction of Arrival (DOA) of acoustic wavefronts. Each sensor station produces a three dimensional DOA vector. The estimated DOA vectors at each time instant are combined to calculate the location of the sound sound source.
The performance of the system was determined using a set of predefined metrics. Using multiple metrics enables one to evaluate the performance of the localization system from different viewpoints. The overall performance is characterized by RMS error between estimates and reference positions. The results show that the performance of the proposed system is consistent and accuracy is satisfactory for meeting room scenario. However, several improvements can be seen.
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Parviainen, M., Pirinen, T., Pertilä, P. (2006). A Speaker Localization System for Lecture Room Environment. In: Renals, S., Bengio, S., Fiscus, J.G. (eds) Machine Learning for Multimodal Interaction. MLMI 2006. Lecture Notes in Computer Science, vol 4299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11965152_20
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DOI: https://doi.org/10.1007/11965152_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69267-6
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