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This paper deals with automatic generation of fundamental frequency (F0) contours for standard Arabic language. We use synthesis by rule for modelling Arabic intonation. The proposed model is based on the assumption that linguistic information is contained in target points of intonative contour. The perception of Arabic lexical accent is correlated with(More)
In this paper, we propose a model to generate fundamental frequency (F0) contours using neural networks. A learning procedure is proposed as an alternative to synthesis-by-rules. The generation of correct fundamental frequency contour is one of the important issues in the naturalness of automatic text-to-speech conversion systems. The proposed approach is(More)
Frequent graph mining is an important though computationally hard problem because it requires enumerating possibly an exponential number of candidate subgraph patterns, and checking their presence in a database of graphs. In this paper, we propose a novel approach for parallel graph mining on GPUs, which have emerged as a relatively cheap but powerful(More)
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