Topic segmentation traditionally relies on lexical cohesion measured through word re-occurrences to output a dense segmentation, either linear or hierarchical. In this paper, a novel organization of the topical structure of textual content is proposed. Rather than searching for topic shifts to yield dense segmentation, we propose an algorithm to extract topically focused fragments organized in ...

In this paper, we present an innovative topic segmentation system based on a new informative similarity measure that takes into account word co-occurrence in order to avoid the accessibility to existing linguistic resources such as electronic dictionaries or lexico-semantic databases such as thesauri or ontology. Topic Segmentation is the task of breaking documents into topically coherent multi...

Lexical dependencies abound in natural language: words tend to follow particular words or word categories. However, artificial language learning experiments exploring word segmentation have so far lacked such structure. In the present study, we explore whether simple inter-word dependencies influence the word segmentation performance of adult learners. We use a continuous testing paradigm inste...

Long sentence analysis has been a critical problem because of high complexity. This paper addresses the reduction of parsing complexity by intra-sentence segmentation, and presents maximum entropy model for determining segmentation positions. The model features lexical contexts of segmentation positions, giving a probability to each potential position. Segmentation coverage and accuracy of the ...

We present a domain-independent unsupervised topic segmentation approach based on hybrid document indexing. Lexical chains have been successfully employed to evaluate lexical cohesion of text segments and to predict topic boundaries. Our approach is based in the notion of semantic cohesion. It uses spectral embedding to estimate semantic association between content nouns over a span of multiple...

This paper presents an unsupervised and incremental model of learning segmentation that combines multiple cues whose use by children and adults were attested by experimental studies. The cues we exploit in this study are predictability statistics , phonotactics , lexical stress and partial lexical information . The performance of the model presented in this paper is competitive with the state-o...

The Role of the Syllable in Speech Segmentation In previous papers we proposed that the syllable is a natural unit in speech processing (Mehler, Segui, and Frauenfelder 1981; Mehler 1981; Segui 1984). According to this position, syllabic units are constructed from the continuous speech signal and constitute the input for lexical access and eventually for more detailed phonemic analysis. This hy...

This dissertation explores effects of speech perception strategies upon morphological structure. Two factors known to be relevant to the segmentation of words from the speech stream are investigated one prelexical, and one lexical. Prelexically, I examine the role of probabilistic phonotactics. At the lexical level, I investigate the role of lexical frequency. I argue that both factors exert a ...

The influence of Malay language into modeling a Malay speech lexicon can be potentially useful for a more accurate transcription and segmentation. The problem arises when trying to discriminate the boundaries between similar sounding phonemes for segmentation, especially in dyslexic children‘s speech when reading, which have been influenced by the surrounding phonemes (before and after) thus ma...

The Role of the Syllable in Speech Segmentation In previous papers we proposed that the syllable is a natural unit in speech processing (Mehler, Segui, and Frauenfelder 1981; Mehler 1981; Segui 1984). According to this position, syllabic units are constructed from the continuous speech signal and constitute the input for lexical access and eventually for more detailed phonemic analysis. This hy...