Nick Jui-Chang Wang

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We h a ve extended the Philips large-vocabulary continuous-speech recognition system towards Chinese. On the way from our existing Western-language technology to Mandarin, the rst step was to build a suitable phonetic model. This paper describes the development of our phonetic model (excluding tones) for Mandarin Chinese. We will present a systematic(More)
Automatic speech recognition (ASR) is a technology which converts the phrases or words spoken by human into text. As a mature technology, ASR has become an alternative input method on many mobile devices, complementing the other input methods operated by hands. Although the technology has been developed for years, the accuracy and computational complexity(More)
Tone modeling is a critical component for Mandarin large-vocabulary continuous-speech recognition systems. In previous work on pitch-feature extraction, we reported character error rate reductions of over 30 over the non-tonal baseline 1. In this paper, we i n vestigate how best to integrate tone modeling with a Mandarin LVCSR system. The paper focusses on(More)
The paper presents a novel approach, integrating layer concept information into the trigram language model, to improve the understanding accuracy for spoken dialogue systems. With this approach, both the recognition accuracy and out-of-grammar problem can be largely improved. The concept error rate is therefore reduced. In the experiment using a real-world(More)
This paper describes the Philips Large Vocabulary Continuous Mandarin speech recognition system for the 1999 Taiwan benchmark. The basic system architecture is based on the Philips LVCSR technology developed for Western languages. However, several modifications are made in order to better suitted processing Chinese spoken languages. In the paper, we present(More)