کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4973683 1451682 2017 34 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
PLDA-based mean shift speakers' short segments clustering
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
PLDA-based mean shift speakers' short segments clustering
چکیده انگلیسی
This paper extends upon a previous work using Mean Shift algorithm to perform speaker clustering on i-vectors generated from short speech segments. In this paper we examine the effectiveness of probabilistic linear discriminant analysis (PLDA) scoring as the metric of the mean shift clustering algorithm in the presence of different numbers of speakers. Our proposed method, combined with k-nearest neighbors (kNN) for bandwidth estimation, yields better and more robust results in comparison to the cosine similarity with fixed neighborhood bandwidth for clustering segments of large numbers of speakers. In the case of 30 speakers, we achieved significant improvement in cluster and speaker purity with the PLDA-based mean shift algorithm compared to the cosine-based baseline system.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Speech & Language - Volume 45, September 2017, Pages 411-436
نویسندگان
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