a thorough recognition of the nature and duties of the genes is based upon having adequate information about the proteins. however, the proteomic projects follow a slow trend; therefore, solving the protein-related problems has become as one of the most important challenges in bio-informatics. consequently, the presence of tools which can enhance the structural recognition, classification, and ...

Hidden Markov models are powerful tools for acoustic modeling in speech recognition systems. However, detailed analysis of their performance in specific experiments can be difficult. Two tools were developed and implemented for the purpose of analyzing hidden Markov model experiments: an interactive Viterbi backtrace viewer, and a multi-dimensional scaling display. These tools were built using ...

speech emotion can add more information to speech in comparison to available textual information. however, it will also lead to some problems in speech recognition process. in a previous study, we depicted the substantial changes of speech parameters caused by speech emotion. therefore, in order to improve emotional speech recognition rate, in a first step, the effects of emotion on speech par...

This paper gives an overview of our research on Chinese spoken language technologies during the past ten years. It covers fundamental acoustic-phonetic studies of spoken Cantonese, speech corpora development, automatic speech recognition and text-to-speech. Currently our focus is on making these technologies more usable for general users who are not speech experts, and more robust for real-worl...

This short paper analyses an experiment comparing the efficacy of several Named Entity Recognition (NER) tools at extracting entities directly from the output of an optical character recognition (OCR) workflow. The authors present how they first created a set of test data, consisting of raw and corrected OCR output manually annotated with people, locations, and organizations. They then ran each...

Deep neural networks (DNN) are special forms of learning-based structures composed of multiple hidden layers formed by artificial neurons. These are different to the conventional artificial neural networks (ANN) and are accepted as efficient tools for solving emerging real world problems. Recently, DNNs have become a mainstream speech recognition tool and are fast becoming part of evolving tech...

Neuropsychological and neuroimaging research has established that knowledge related to tool use and tool recognition is lateralized to the left cerebral hemisphere. Recently, behavioural studies with the visual half-field technique have confirmed the lateralization. A limitation of this research was that different sets of stimuli had to be used for the comparison of tools to other objects and o...