A motor theory of speech perception, initially proposed to account for results of early experiments with synthetic speech, is now extensively revised to accommodate recent findings, and to relate the assumptions of the theory to those that might be made about other perceptual modes. According to the revised theory, phonetic information is perceived in a biologically distinct system, a ‘module ’ specialized to detect the intended gestures of the speaker that are the basis for phonetic categories. Built into the structure of this module is the unique but lawful relationship between the gestures and the acoustic patterns in which they are variously overlapped. In consequence, the module causes perception of phonetic structure without translation from preliminary auditory impressions. Thus, it is comparable to such other modules as the one that enables an animal to localize sound. Peculiar to the phonetic module are the relation between perception and production it incorporates and the fact that it must compete with other modules for the same stimulus variations.

Speech rhythm in the different Arabic dialects investigated has been consistently described as stress-timed. At the same time, there is preliminary evidence from perceptual experiments that listeners use speech rhythm cues to distinguish speakers from North Africa from those of the Middle East

created. Finally, we sketch how these resources and tools are put together to create DIRA, a term-expansion tool for information retrieval over dialectal Arabic collections using Modern Standard Arabic queries. 1.

Arabic dialect classification has been an important and challenging problem for Arabic language processing, especially for social media text analysis and machine translation. In this paper we propose an approach to improving Arabic dialect classification with semi-supervised learn-ing: multiple

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We study the effectiveness of recently developed language recognition techniques based on speech recognition models for the discrimination of Arabic dialects. Specifically, we investi-gate dialect-specific and cross-dialectal phonotactic models, us-ing both language models and support vector

2009 c ○ by respective authors The articles can be used under the

Arabic is not just one language, but rather a collection of dialects in addition to Modern Standard Arabic (MSA). While MSA is used in formal situations, dialects are the language of every day life. Until recently, there was very little dialectal Arabic in written form. With the advent of social

Most theories of spoken word identification assume that variable speech signals are matched to canonical representations in memory. To achieve this, idiosyncratic voice details are first normalized, allowing direct comparison of the input to the lexicon. This investigation assessed both explicit

In the Arab world, while Modern Standard Arabic is commonly used in formal written context, on sites like Youtube, people are increasingly using Dialectal Arabic, the language for everyday use to comment on a video and interact with the community. These user-contributed comments along