[Hidden Word]

Spoken Word Recognition Using Hidden Markov Model

VI

Word confusability - measuring hidden Markov model similarity

We address the problem of word confusability in speech recognition by measuring the similarity between Hidden Markov Models (HMMs) using a number of recently developed techniques. The focus is on defining a word confusability that is accurate, in the sense of predicting artificial speech recognition errors, and computationally efficient when applied to speech recognition applications. It is sho...

Hidden Markov Tree Model for Word Alignment

We propose a novel unsupervised word alignment model based on the Hidden Markov Tree (HMT) model. Our model assumes that the alignment variables have a tree structure which is isomorphic to the target dependency tree and models the distortion probability based on the source dependency tree, thereby incorporating the syntactic structure from both sides of the parallel sentences. In English-Japan...

Automatic Word Spacing Using Hidden Markov Model

Japanese Word Segmentation by Hidden Markov Model

The processing of Japanese text is complicated by the fact that there are no word delimiters. To segment Japanese text, systems typically use knowledge-based methods and large lexicons. This paper presents a novel approach to Japanese word segmentation which avoids the need for Japanese word lexicons and explicit rule bases. The algorithm utilizes a hidden Markov model, a stochastic process, to...