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Isolated Word Recognition (IWR) is becoming increasingly attractive due to the improvement of speech recognition techniques. However, the accuracy of IWR suffers when large databases or words with similar pronunciation are used. The criterion for accurate speech recognition is suitable segmentation. However, the traditional method of segmentation equal segmentation does not produce the most accurate result. Furthermore, utilizing manual segmentation based on events is not possible in large databases. In this paper, we introduce an intelligent segmentation based on Hierarchical Temporal Decomposition (HTD). Based on this method, a temporal decomposition (TD) algorithm can be used to... 

In recent years, IWR (Isolated Word Recognition) was one of the main concerns of speech processing. The challenging problems in this field appear when the database become so large or when we have a lot of word with similarly pronounce in the database. This paper introduces a general solution for a traditional problem in isolated similarly pronounced word recognition, especially in large databases. One the important problem of traditional IWR is referred to their segmentation algorithm, their methods were lacking in efficiency due to the following reasons: First, using equal segmentation is not at all intelligent at all and as a result, cannot produce accurate results; besides, utilizing...