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In this paper, we present a novel approach for morphological decomposition in large vocabulary Arabic speech recognition. It achieved low out-of-vocabulary (OOV) rate as well as high recognition accuracy in a state-of-the-art Arabic broadcast news transcription system. In this approach, the compound words are decomposed into stems and affixes in both(More)
In this paper, we describe the use of either words or morphemes as lexical modeling units and the use of either graphemes or phonemes as phoneticmodeling units for Arabic automatic speech recognition (ASR). We designed four Arabic ASR systems: two word-based systems and two morpheme-based systems. Experimental results using these four systems show that they(More)
This paper presents a set of experiments that we conducted in order to optimize the performance of an Arabic/English machine translation system on broadcast news and conversational speech data. Proper integration of speech-to-text (STT) and machine translation (MT) requires special attention to issues such as sentence boundary detection, punctuation, STT(More)
The majority of state-of-the-art speech recognition systems make use of system combination. The combination approaches adopted have traditionally been tuned to minimising word error rates (WERs). In recent years there has been a growing interest in taking the output from speech recognition systems in one language and translating it into another. This paper(More)
In this paper, we describe the BBN 2007 Mandarin speech-to-text system developed for the GALE Evaluation 2007. In comparison to the BBN 2006 Mandarin system, we achieved 25% relative reduction in character error rate on the most important test sets. The utilization of all available training data provided the largest contribution to the improvement. The use(More)
We show the progress for Arabic speech recognition by incorporating contextual information into the process of morphological decomposition. The new approach achieves lower out-of-vocabulary and word error rates when compared to our previous work, in which the morphological decomposition relies on word-level information only. We also describe how the(More)
The purpose of this study was to evaluate the differences between volumetric modulated arc therapy (VMAT) and intensity-modulated radiation therapy (IMRT) in the treatment of nasal cavity carcinomas. The treatment of 10 patients, who had completed IMRT treatment for resected tumors of the nasal cavity, was replanned with the Philips Pinnacle(3) Version 9(More)
In this paper, we show the progress for Arabic speech recognition by incorporating contextual information into the process of morphological decomposition. The new approach achieves lower out-of-vocabulary and word error rates when compared to our previous work, in which the morphological decomposition relies on word-level information only. We also describe(More)
In this paper, we present a method to extract probabilistic acoustic features by using the Adaptive Boosting algorithm (AdaBoost). We build phoneme Gaussian mixture classifiers, and use AdaBoost to enhance the classification performance. The outputs from AdaBoost are the posterior probabilities for each frame given all phonemes. Those posterior features are(More)
UNLABELLED New recommendations for the validation of rapid microbiological methods have been included in the revised Technical Report 33 release from the PDA. The changes include a more comprehensive review of the statistical methods to be used to analyze data obtained during validation. This case study applies those statistical methods to accuracy,(More)
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