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The recognition of speech in meetings poses a number of challenges to current Automatic Speech Recognition (ASR) techniques. Meetings typically take place in rooms with non-ideal acoustic conditions and significant background noise, and may contain large s ...
Tasks that rely on semantic content of documents, notably Information Retrieval and Document Classification, can benefit from a good account of document context, i.e. the semantic association between documents. To this effect, the scheme of latent semantic ...
We first present our work in machine translation, during which we used aligned sentences to train a neural network to embed n-grams of different languages into an d-dimensional space, such that n-grams that are the translation of each other are close with ...
Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...
Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...
Domain adaptation of a language model aims at re-estimating word sequence probabilities in order to better match the peculiarities of a given broad topic of interest. To achieve this task, a common strategy consists in retrieving adaptation texts from the ...
In this paper, we present a robust speech acquisition system to acquire continuous speech using a microphone array. A microphone array based speech recognition system is also presented to study the environmental interference due to reverberation, backgroun ...
This thesis presents a PhD work on offline cursive handwriting recognition, the automatic transcription of cursive data when only its image is available. Two main approaches were used in the literature to solve the problem. The first one attempts to segmen ...
This paper describes a system that recognizes hand-printed digits. The system is based on optimal bounded error matching, a technique already in common use in general-purpose 2D and 3D visual object recognition systems in cluttered, noisy scenes. In this p ...
This paper describes a system for recognizing hand-printed digits using optimal bounded error matching. Bounded error matching is already in common use in general-purpose 2D and 3D visual object recognition and can cope with clutter, occlusions, and noise, ...
