Regularized Least Squares-Based Method for Optimal Fusion of Speech Pitch Detection Algorithms

سال انتشار: 1397
محل انتشار: چهارمین کنفرانس پردازش سیگنال و سیستم‌های هوشمند
کد COI اختصاصی: SPIS04_049
زبان مقاله: انگلیسی
تعداد مشاهده: 525

نویسندگان

چکیده

Fundamental frequency estimation is one of the most important issues in the field of speech processing. An accurate estimate of the fundamental frequency plays akey role in the field of speech and music analysis. So far, various methods have been proposed in the time- and frequency-domain. However, the main challenge is thestrong noises in speech signals. In this paper, to improve the accuracy of fundamental frequency estimation, we propose method for optimal combination of fundamentalfrequency estimation methods, in noisy signals. In this method, to discriminate voiced frames from unvoiced frames in better way, the Voiced/Unvoiced (V/U) scores of four pitch detection methods are combined linearly. These methods are: Autocorrelation, Yin, YAAPT and SWIPE. After identifying the Voiced/Unvoiced label of each frame, the fundamental frequency (F0) of the frame is estimated using the SWIPE method. The optimal coefficients for linear combination are determined using the regularized least squares method with Tikhonov regularization. To evaluate the proposed method, 10 speech files (5 female and male voices) are selected from the PTDB-TUG standard database and the results are presented in terms of SDFPE, GPE, VDE, PTE and FFE standard error criteria. The results indicate that our proposed method relatively reduced the aforementioned criteria (averaged in various SNRs) by 27.13%, 22.14%, 17.40%, and 26.74% respectively, which demonstrate the effectiveness of the proposed method in comparison to state-of-the-art methods.

کلیدواژه ها

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.