Support Vector Machines for Speaker Based Speech Indexing
Publish place: 14th annual International CSI Computer Conference
Publish Year: 1388
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CSICC14_088
تاریخ نمایه سازی: 24 خرداد 1388
Abstract:
This paper proposes an integrated framework for speaker indexing which includes both speaker segmentation and speaker clustering. Speaker indexing systems has wide domains of application with different requirements which make a general speaker indexing framework hard to accomplish. The main source of performance degradation in speaker indexing is the probable existence of short speech utterances which makes the speaker turns hard to distinguish and also exposes the segment modeling to data insufficiency. This paper introduces a speaker indexing framework with high average performance which uses Support Vector Machines (SVM) as the core approach. The main contribution of this framework is the SVM based clustering approach which makes the indexing more robust against the short speech segments. This framework is evaluated on a domestic conversational speech dataset and the results were satisfactory.
Authors
M.H Moattar
Laboratory for Intelligent Signal and speech Processing,Computer Enginerring and IT Dept., Amirkabir University of Technology, Tehran, Iran
M.M Homayounpour
Laboratory for Intelligent Signal and speech Processing,Computer Enginerring and IT Dept., Amirkabir University of Technology, Tehran, Iran