Karim Filali

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Sitting at the intersection between statistics and machine learning, Dynamic Bayesian Networks have been applied with much success in many domains, such as speech recognition, vision, and computational biology. While Natural Language Processing increasingly relies on statistical methods, we think they have yet to use Graphical Models to their full(More)
In recent years there has been growing interest in discriminative parameter training techniques, resulting from notable improvements in speech recognition performance on tasks ranging in size from digit recognition to Switchboard. Typified by Maximum Mutual Information (MMI) or Minimum Classification Error (MCE) training, these methods assume a fixed(More)
We investigate a highly effective and extremely simple noiserobust front end based on novel post-processing of standard MFCC features on the Aurora databases. It performs remarkably well on both the Aurora 2.0 and Aurora 3.0 databases without requiring any increase in model complexity. Our experiments on Aurora 2.0 have been reported in [1]. In this paper,(More)
In recent years there has been growing interest in discriminative parameter training techniques, resulting from notable improvements in speech recognition performance on tasks ranging in size from digit recognition to Switchboard. Typified by Maximum Mutual Information training, these methods assume a fixed statistical modeling structure, and then optimize(More)
It is important to produce automatic speech recognition (ASR) systems that use as few computational and memory resources as possible, especially in low-memory/low-power environments such as for personal digital assistants. One way to achieve this is through parameter quantization. In this work, we compare a variety of novel subvector clustering procedures(More)
We present a probabilistic model of a user's search history and a target query reformulation. We derive a simple transitive similarity algorithm for disambiguating queries and improving history-based query reformulation accuracy. We compare the merits of this approach to other methods and present results on both examples assessed by human editors and on(More)
BACKGROUND Exertional heat stroke (EHS) is still a main cause of death in sport. Many of EHS complications could have been prevented if EHS had been recognized and treated early and properly. CASE PRESENTATION We report an unusual case of multiple organ failure caused by EHS due to intensive sportive activities in a hot environment with lack of primary(More)
There is fast growing research on designing energy-efficient computational devices and applications running on them. As one of the most compelling applications for mobile devices, automatic speech recognition (ASR) requires new methods to allow it to use fewer computational and memory resources while still achieving a high level of accuracy. One way to(More)
Tuberculosis remains a global threat to public health. Considerable efforts have been made to combat this disease. However, the emergence ofMycobacterium tuberculosis (Mtb) strains resistant to the major anti-tuberculosis drugs especially multidrug resistant (MDR) strains poses a deadly threat to control programs. The present study aims to identify the most(More)