Roadmapping an emerging energy technology: An ex-ante examination of dimethyl ether development in China

Technology roadmapping has been used to strategise the development of energy technologies. However, there have been limited roadmapping applications that analyse the emergence of a new energy technology that then forms a new industry and propels broad-based low-carbon economic growth. This paper, therefore, attempts to develop a roadmapping framework by integrating the lifecycle analysis tool, in order to strategise the emergence of dimethyl ether, an alternative energy based on advanced engineering technologies such as carbon capture and storage. This paper compares two scenarios of dimethyl ether vs. diesel and finds that the superiority of dimethyl ether will not arise until 2030, when the complementary engineering technologies become available. This proposed framework can also be generalised to other clean energy industries, and we anticipate our paper will spark inspiration for roadmapping and strategising the 'right' technologies for the growth of Chinese energy industries. Copyright © 2012 Inderscience Enterprises Ltd.

Exploiting Chinese character models to improve speech recognition performance

The Chinese language is based on characters which are syllabic in nature. Since languages have syllabotactic rules which govern the construction of syllables and their allowed sequences, Chinese character sequence models can be used as a first level approximation of allowed syllable sequences. N-gram character sequence models were trained on 4.3 billion characters. Characters are used as a first level recognition unit with multiple pronunciations per character. For comparison the CU-HTK Mandarin word based system was used to recognize words which were then converted to character sequences. The character only system error rates for one best recognition were slightly worse than word based character recognition. However combining the two systems using log-linear combination gives better results than either system separately. An equally weighted combination gave consistent CER gains of 0.1-0.2% absolute over the word based standard system. Copyright © 2009 ISCA.