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Due to the short length, diversity, openness and colloquialism characteristic of out-of-domain (OOD) utterances, dialogue act (DA) recognition for OOD utterances in restricted domain spoken dialogue system remains a great challenge. This paper tackles this problem by proposing an effective DA recognition method using hybrid convolutional neural network (CNN) and random forest (RF). CNN acts as a feature...
The aim of this paper is to develop a system that involves character recognition of Brahmi, Grantha and Vattezuthu characters from palm manuscripts of historical Tamil ancient documents, analyzed the text and machine translated the present Tamil digital text format. Though many researchers have implemented various algorithms and techniques for character recognition in different languages, ancient...
In this paper, we investigate a range of strategies for combining multiple machine learning techniques for recognizing Arabic characters, where we are faced with imperfect and dimensionally variable input characters. Experimental results show that combined confidence-based backoff strategies can produce more accurate results than each technique produces by itself and even the ones exhibited by the...
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