78 % on a given short phrase. This paper submits the result of our analysis of the three algorithms to investigate their growth pattern and decide which of the three is the fastest in making decision of vowel recognition. The simple system of vowel recognition, presented in this paper, which leads

I present an entropy measure for evaluating parser performance. The measure is fine-grained, and permits us to evaluate performance at the level of individual phrases. The parsing problem is characterized as statistically approximating the Penn Treebank annotations. I consider a series of models

The paper presents a simple algorithm to cull short phrases of interest spoken in a long recorded speech. Listening to a long and boring recording of a suspect who is being wiretapped may irk intelligence investigator if it does not contain any speech segment of interest. It would be much useful

We present a phrase recognition system based on perceptrons, and an online learning algorithm to train them together. The recognition strategy applies learning in two layers, first at word level, to filter words and form phrase candidates, second at phrase level, to rank phrases and select

We present a phrase recognition system based on perceptrons, and an online learning algorithm to train them together. The recognition strategy applies learning in two layers, first at word level, to filter words and form phrase candidates, second at phrase level, to rank phrases and select

The performance of machine learning algorithms can be improved by combining the output of different systems. In this paper we apply this idea to the recognition of noun phrases. We generate different classifiers by using different representations of the data. By combining the results with voting

The performance of machine learning algorithms can be improved by combining the output of different systems. In this paper we apply this idea to the recognition of noun phrases. We generate different classifiers by using different representations of the data. By combining the results with voting

knowledge base extracted from Wikipedia. In this paper we evaluate the impact of the phrase recognition step on the ability of the system to correctly reproduce the annotations of a gold standard in an unsupervised setting. We argue that a combination of techniques is needed, and we evaluate a number

This work presents an architecture based on perceptrons to recognize phrase structures, and an online learning algorithm to train the perceptrons together and dependently. The recognition strategy applies learning in two layers: a filtering layer, which reduces the search space by identifying

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