教師資料查詢 | 類別: 期刊論文 | 教師: 陳麗菁 Li Ching Chen (瀏覽個人網頁)

標題:A New Method for Measuring Similarity Between Two GMMs
學年99
學期2
出版(發表)日期2011/06/01
作品名稱A New Method for Measuring Similarity Between Two GMMs
作品名稱(其他語言)
著者Ting, Chuan-Wei; Chen, Li-Ching; He, Chih-Liang
單位淡江大學統計學系
出版者Toroku: ICIC International
著錄名稱、卷期、頁數ICIC Express Letters 5(6), pp.1839-1844
摘要This study presents a new method for measuring similarity between two Gaussian mixture models (GMMs) to discover how to compensate for variations in the topology of adaptive hidden Markov models (HMM). The aims of the proposed scheme is to determine whether a new state topology with different variations should be added to existing acoustic models in response to the addition of training data. The testing of two Gaussian densities is frequently used in the sharing of parameters between Gaussian components of HMM. In this work, we extend such hypothesis to measure similarities between two GMMs and estimate the statistic from the proposed test through the summation of two gamma distributions. A new HMM topology is automatically generated according to a level of significance. The dataset-dependent characteristics and variations are handled with an adaptive HMM topology. Experiments on speech recognition tasks show that the proposed testing scheme performs significantly better than the standard HMM with a comparable size of parameters.
關鍵字
語言英文
ISSN1881-803X
期刊性質國外
收錄於EI;
產學合作
通訊作者
審稿制度
國別日本
公開徵稿
出版型式,紙本
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