Wen-Yuan Liao

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Automatic emotional speech recognition system can be characterized by the selected features, the investigated emotional categories, the methods to collect speech utterances, the languages, and the type of classifier used in the experiments. Until now, several classifiers are adopted independently and tested on numerous emotional speech corpora but no any(More)
Automatic recognition of emotions in speech aims at building classifiers for classifying emotions in test emotional speech. This paper presents an emotion recognition system to compare several classifiers from clean and noisy speech. Five emotions, including anger, happiness, sadness, neutral and boredom, from Mandarin emotional speech are investigated. The(More)
The technique of motion vector estimation can remove the information of temporal redundancy to reduce the bit rate for video coding. Due to the great computation required in motion vector estimation, many simplified search algorithms have been proposed. In particular, one-bit transform scheme can significantly reduce the search complexity. This paper(More)
This paper presents a Mandarin audio-visual recognition system dealing with noisy and emotional speech signal. In the proposed approach, we extract the visual features of the lips. These features are very important to the recognition system especially in noisy condition or with emotional effects. In this recognition system, we propose to use the(More)
Automatic speech recognition (ASR) by machine has been a goal and an attractive research area for past several decades. In recent years, there has been growing attractive research topic for overcoming certain audio-only recognition problems. Motivated by the multimodal nature of speech, the visual feature is considered to bring in information that dose not(More)
Automatic speech recognition (ASR) by machine has been an attractive research area in past several decades. In recent years, there are many automatic speech-reading systems proposed that utilizing the combination of audio and visual speech features. In this paper, we proposed an automatic visual feature extraction approach to extract the visual features of(More)
Speech signal is a rich source of information and convey more than spoken words, and can be divided into two main groups: linguistic and nonlinguistic. The linguistic aspects of speech include the properties of the speech signal and word sequence and deal with what is being said. The nonlinguistic properties of speech have more to do with talker attributes(More)
Exploring vehicle emission trends within and outside the Pearl River Delta (PRD) region during a long period was scientific and practical, for the economic rapid unbalanced development, continuous implements of severe reducing vehicle emissions measures in Guangdong province. Multi-year inventories of vehicle emissions from 1994 to 2014 were estimated based(More)