Vowel Recognition based on FLAC Acoutic Features and Subspace Classifier

摘要：

An approach is proposed in this paper for vowel recognition. For extracting the features of vowels, we employ the time-frequency feature extraction method (FLAC) which computes local auto-correlations on complex Fourier values. The FLAC feature takes advantage of both magnitude and phase information and extracts temporal dynamics in time and frequency domains. At recognition stage, we develop a (complex) subspace classifier to categorize the input vowels based on exploring the deviation distances from the test vowel to the trained vowel subspaces. We evaluate the proposed method by conducting experiments on a Japanese vowel dataset. The comparison experiments demonstrate the effectiveness of the proposed approach.

关键词： vowel recognition time frequency analysis all phase FFT local auto-correlation subspace classifier

作者: Jiaxing Ye Takumi Kobayashi Tetsuya Higuchi

作者单位: Department of Computer Science University of Tsukuba Tsukuba, Japan National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba, Japan National Institute of Advanced Industrial Science and Technology (AIST) Department of Computer Scien

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 530-533

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）