文章基本信息

标题：Intra-and Inter-frame Features for Automatic Speech Recognition
本地全文：下载
作者：Lee, Sung Joo ; Kang, Byung Ok ; Chung, Hoon 等
期刊名称：ETRI Journal
印刷版ISSN：1225-6463
电子版ISSN：2233-7326
出版年度：2014
卷号：36
期号：3
页码：514-517
DOI：10.4218/etrij.14.0213.0181
语种：English
出版社：Electronics and Telecommunications Research Institute
摘要：In this paper, alternative dynamic features for speech recognition are proposed. The goal of this work is to improve speech recognition accuracy by deriving the representation of distinctive dynamic characteristics from a speech spectrum. This work was inspired by two temporal dynamics of a speech signal. One is the highly non-stationary nature of speech, and the other is the inter-frame change of a speech spectrum. We adopt the use of a sub-frame spectrum analyzer to capture very rapid spectral changes within a speech analysis frame. In addition, we attempt to measure spectral fluctuations of a more complex manner as opposed to traditional dynamic features such as delta or double-delta. To evaluate the proposed features, speech recognition tests over smartphone environments were conducted. The experimental results show that the feature streams simply combined with the proposed features are effective for an improvement in the recognition accuracy of a hidden Markov model-based speech recognizer.
关键词：Speech recognition;feature extraction