{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T18:05:15Z","timestamp":1754157915112,"version":"3.41.2"},"reference-count":14,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2008,6,27]],"date-time":"2008-06-27T00:00:00Z","timestamp":1214524800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,6,27]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to describe a speech and character combined recognition engine (SCCRE) developed for working on personal digital assistants (PDAs) or on mobile devices. Also, the architecture of a distributed recognition system for providing a more convenient user interface is discussed.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>In SCCRE, feature extraction for speech and for character is carried out separately, but the recognition is performed in an engine. The client recognition engine essentially employs a continuous hidden Markov model (CHMM) structure and this CHMM structure consists of variable parameter topology in order to minimize the number of model parameters and to reduce recognition time. This model also adopts the proposed successive state and mixture splitting (SSMS) method for generating context independent model. SSMS optimizes the number of mixtures through splitting in mixture domain and the number of states through splitting in time domain.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The recognition results show that the developed engine can reduce the total number of Gaussian up to 40 per cent compared with the fixed parameter models at the same recognition performance when applied to speech recognition for mobile devices. It shows that SSMS can reduce the size of memory for models to 65 per cent and that for processing to 82 per cent. Moreover, the recognition time decreases 17 per cent with the SMS model while maintaining the recognition rate.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The proposed system will be very useful for many on\u2010line multimodal interfaces such as PDAs and mobile applications.<\/jats:p><\/jats:sec>","DOI":"10.1108\/17427370810890409","type":"journal-article","created":{"date-parts":[[2008,8,16]],"date-time":"2008-08-16T07:18:36Z","timestamp":1218871116000},"page":"232-249","source":"Crossref","is-referenced-by-count":1,"title":["A speech and character combined recognition engine for mobile devices"],"prefix":"10.1108","volume":"4","author":[{"given":"Soo\u2010Young","family":"Suk","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyun\u2010Yeol","family":"Chung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2021010501513071900_b1","unstructured":"Biem, A., Ha, J.Y. and Subrahmonia, J. (2002), \u201cA Bayesian model selection criterion for HMM topology optimization\u201d, ICASSP Proceedings, pp. 989\u201092."},{"key":"key2021010501513071900_b2","unstructured":"Deng, L. (2002), \u201cDistributed speech processing in mipad's multimodal user interface\u201d, IEEE on Transactions Speech and Audio., Vol. 10 No. 8, pp. 605\u201019."},{"key":"key2021010501513071900_b3","unstructured":"Heo, S.H. (2003), \u201cMultiple pitch candidates based music information retrieval method for query\u2010by\u2010humming\u201d, AMR Proceedings, Vol. 1, pp. 189\u2010200."},{"key":"key2021010501513071900_b4","unstructured":"Li, D., Biem, A. and Subrahmonia, J. (2001), \u201cHmm topology optimization for handwriting recognition\u201d, ICASSP Proceedings."},{"key":"key2021010501513071900_b5","doi-asserted-by":"crossref","unstructured":"Nakagawa, S. (1983), \u201cA connected spoken word recognition method by O(n) dynamicprogramming pattern matching algorithm\u201d, ICASSP Proceedings, pp. 296\u20109.","DOI":"10.1109\/ICASSP.1983.1172219"},{"key":"key2021010501513071900_b6","unstructured":"Ralph, G., Stefan, M. and Alex, W. (1997), Run\u2010on Recognition in an On\u2010line Handwriting Recognition System, Carnegie Mellon Univ Press."},{"key":"key2021010501513071900_b7","unstructured":"Sin, B.K. and Kim, J. (1993), \u201cA statistical approach with HMMs for online cursive hangul (Korean Script) recognition\u201d, Second International Conference on Document Analysis and Recognition Proceedings, Zuchuba, Japan, pp. 147\u201050."},{"key":"key2021010501513071900_b8","doi-asserted-by":"crossref","unstructured":"Singer, H. and Ostendorf, M. (1996) \u201cMaximum likelihood successive state splitting\u201d, ICASSP Proceedings, Vol. 2, pp. 601\u20104.","DOI":"10.1109\/ICASSP.1996.543192"},{"key":"key2021010501513071900_b9","unstructured":"Suk, S.Y., Kim, M.J. and Chung, H.Y. (2002), \u201cAn on\u2010line speech and character combined recognition system for multimodal interfaces\u201d, EALPIIT Proceedings, pp. 89\u201092."},{"key":"key2021010501513071900_b10","unstructured":"Takami, J. and Sagayama, S. (1992), \u201cA successive state splitting algorithm for efficient allophone modeling\u201d, ICASSP Proceedings, Vol. 1, pp. 573\u201076."},{"key":"key2021010501513071900_b11","unstructured":"Takaki, H., Mashahru, K., Akinori, I. and Masaki, K. (1997), \u201cA study on HMNets using decision tree\u2010based successive splitting\u201d, ICSP\u201097 Proceedings, pp. 383\u20107."},{"key":"key2021010501513071900_b12","unstructured":"Tong, H. (1975), \u201cDetermination of the order of a markov chain by Akaike's information criterion\u201d, Journal of Applied Probability, Vol. 12, pp. 488\u201097."},{"key":"key2021010501513071900_b13","unstructured":"VoiceXML Forum (2003), \u201cVoice extensible markup language 2.0\u201d, VoiceXML Forum, available at: www.voicexml.org"},{"key":"key2021010501513071900_b14","unstructured":"Suk, S.Y., Jung, H.Y., Makino, S. and Chung, H.Y. (2004), \u201cDistributed speech recognition system for PDA in wireless network environment\u201d, SPECOM Proceedings."}],"container-title":["International Journal of Pervasive Computing and Communications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/17427370810890409","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/17427370810890409\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/17427370810890409\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T00:24:10Z","timestamp":1753403050000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ijpcc\/article\/4\/2\/232-249\/162791"}},"subtitle":[],"editor":[{"given":"Xioabo","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2008,6,27]]},"references-count":14,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2008,6,27]]}},"alternative-id":["10.1108\/17427370810890409"],"URL":"https:\/\/doi.org\/10.1108\/17427370810890409","relation":{},"ISSN":["1742-7371"],"issn-type":[{"type":"print","value":"1742-7371"}],"subject":[],"published":{"date-parts":[[2008,6,27]]}}}