کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7152494 | 1462399 | 2016 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Stereophonic channel decorrelation using a binaural masking model
ترجمه فارسی عنوان
دکوراسیون کانال استریوفونیک با استفاده از مدل ماسک دو طرفه
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کلمات کلیدی
دکوراسیون کانال، ماساژ دو طرفه، تزریق سینوسی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی مکانیک
چکیده انگلیسی
Traditional methods often only use monaural masking models to decorrelate input signals for stereo acoustic echo cancellation. Whereas, it seems more reasonable to use binaural masking models for the following two reasons. First, stereo signals are heard by two ears rather than just one. Second, psychoacoustic researchers have already shown that there are obvious masking level differences between binaural masking models and monaural masking models. By studying binaural masking level difference models, we first introduce a simplified binaural masking model for stereo acoustic echo cancellation. Considering that the interaural time difference is dominant at low frequencies (⩽1.5 kHz) and the interaural level difference is a major cue at higher frequencies, we propose to use different signal decorrelation schemes at these two frequency bands. In the low-frequency band, a pitch-driven sinusoidal injection scheme is proposed to maintain the interaural time difference, where the amount of injection is determined by the proposed binaural masking model. In the high-frequency band, a modified sinusoidal phase modulation scheme is applied to make a trade-off between preserving the interaural level difference and decorrelating the stereophonic input signals. Assessment results show that the proposed method can effectively improve the non-unique problem and retain good speech quality.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Acoustics - Volume 110, September 2016, Pages 128-136
Journal: Applied Acoustics - Volume 110, September 2016, Pages 128-136
نویسندگان
Hefei Yang, Jie Wang, Chengshi Zheng, Xiaodong Li,