کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6951571 | 1451693 | 2015 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Feature extraction based on the high-pass filtering of audio signals for Acoustic Event Classification
ترجمه فارسی عنوان
استخراج ویژگی بر اساس فیلتر تصویب بالا از سیگنال های صوتی برای طبقه بندی رویداد آکوستیک
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
In this paper, we propose a new front-end for Acoustic Event Classification tasks (AEC). First, we study the spectral characteristics of different acoustic events in comparison with the structure of speech spectra. Second, from the findings of this study, we propose a new parameterization for AEC, which is an extension of the conventional Mel-Frequency Cepstral Coefficients (MFCC) and is based on the high pass filtering of the acoustic event signal. The proposed front-end have been tested in clean and noisy conditions and compared to the conventional MFCC in an AEC task. Results support the fact that the high pass filtering of the audio signal is, in general terms, beneficial for the system, showing that the removal of frequencies below 100-275Â Hz in the feature extraction process in clean conditions and below 400-500Â Hz in noisy conditions, improves significantly the performance of the system with respect to the baseline.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Speech & Language - Volume 30, Issue 1, March 2015, Pages 32-42
Journal: Computer Speech & Language - Volume 30, Issue 1, March 2015, Pages 32-42
نویسندگان
Jimmy Ludeña-Choez, Ascensión Gallardo-AntolÃn,