کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
865674 | 909678 | 2008 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Maximum Likelihood A Priori Knowledge Interpolation-Based Handset Mismatch Compensation for Robust Speaker Identification
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Maximum Likelihood A Priori Knowledge Interpolation-Based Handset Mismatch Compensation for Robust Speaker Identification Maximum Likelihood A Priori Knowledge Interpolation-Based Handset Mismatch Compensation for Robust Speaker Identification](/preview/png/865674.png)
چکیده انگلیسی
Unseen handset mismatch is the major source of performance degradation in speaker identification in telecommunication environments. To alleviate the problem, a maximum likelihood a priori knowledge interpolation (ML-AKI)-based handset mismatch compensation approach is proposed. It first collects a set of handset characteristics of seen handsets to use as the a priori knowledge for representing the space of handsets. During evaluation the characteristics of an unknown test handset are optimally estimated by interpolation from the set of the a priori knowledge. Experimental results on the HTIMIT database show that the ML-AKI method can improve the average speaker identification rate from 60.0% to 74.6% as compared with conventional maximum a posteriori-adapted Gaussian mixture models. The proposed ML-AKI method is a promising method for robust speaker identification.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tsinghua Science & Technology - Volume 13, Issue 4, August 2008, Pages 528-532
Journal: Tsinghua Science & Technology - Volume 13, Issue 4, August 2008, Pages 528-532
نویسندگان
Yuanfu (å»å
ç«), Zhixian (åºæºæ¾), Jyhher (æ¨æºå),