Introduction of the speaking rate in the model of speech recognition

We propose an improvement to the centisecond TLHMM model (Meziane, 1999) applied to the sound duration. Indeed, the distribution of the sound duration depends on the speaking rate. An adaptation in a post-processing step is needed. This adaptation is studied by proposing a model of the speaking rate based on average syllabic duration. The experiments elaborated on a set of BDSONS show the interest of this approach. This work is a continuation of those by Meziane (1999) and Suaudeau (1994)

Quelques resultats nouveaux sur les mesures stationnaires de chaines de Markov denombrables

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Arabic topic detection using automatic text summarisation

With the exponential growth of the online available Arabic documents, classifying and processing large Arabic corpora has became a challenging task. The presence of noisy information embedded in these documents has made it even more difficult to get accurate results when applying a Topic Detection (TD) process. To address this problem, a proper features selection approach is needed to enhance the topic detection accuracy. In this paper, we explore the impact of using automatic summarisation technique along with a feature-selection process to enhance Arabic Topic Detection. In our work we show that using automatic summarisation reduces noisy information and results in a significant enhancement to the topic detection process and therefore increases the performance of our TD system. This was achieved by the ability of our summariser system in reducing documents size to speed up the detection process