A Classification Method for Environmental Audio Data

摘要：

In area environment, variations of life form can exhale difference kind of audio signals, and these audio signals are nearly correlative with different biologic subsistence conditions and human activities. To analyze these audio signals automatically, in this paper, we propose a method, which employ effective segment length of audio data (ESLOAD), frequency component of maximum harmonic weight (FCOMHW) in the segment and first order difference Mel-frequency cepstral coefficients matrix (D-MFCCM) to classify area environmental audio data. In the method, it is used for short-time average magnitude to effectively segment the audio data, firstly; then FFT to calculate FCOMHW in the segment; finally, calculate D-MFCCM. For classifying operation, according to ESLOAD and FCOMHW, we confirm the searching range of every segment, individually confirm the segment possible audio type with corresponding D-MFCCM, and then confirm the possible audio types. Through the experiment of 9 categories total 107 normal area environmental audio data, it is indicated the method is effective to classify area environmental audio data.

关键词： audio data segment frequency component maximum harmonic weight Mel-frequency cepstral coefficient

作者: Ying Li

作者单位: College of Mathematics and Computer Science Fuzhou University, Fuzhou 350108, China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 355-361

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）