{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T06:41:12Z","timestamp":1698043272243},"reference-count":12,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2007,3,22]],"date-time":"2007-03-22T00:00:00Z","timestamp":1174521600000},"content-version":"vor","delay-in-days":6289,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems &amp;amp; Computers in Japan"],"published-print":{"date-parts":[[1990,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper describes a new syllable recognition method using the integrated neural network (INN). In this method, the recognition targets are partitioned into several groups. INN consists of a control network and several subnetworks. The control network identifies to which group the input speech belongs, and the subnetworks recognize the syllables within each group. Using INN, even if the recognition scope is large, or even if there are few training samples, the network can recognize syllables with higher recognition accuracy than conventional back\u2010propagation networks. Furthermore, new vocabulary entries can easily be added to an INN by adding new subnetworks corresponding to the new groups. Using the grouping method based on the manner of the articulation of consonants, the recognition accuracy is 96.2 percent for INN, compared with 95.8 percent for the conventional network architecture. This higher accuracy is obtained with 40 percent lower training costs. Using the grouping method based on the hidden layer activation patterns of a network which has learned to recognize all syllables, the accuracy is 96.0 percent.<\/jats:p>","DOI":"10.1002\/scj.4690210909","type":"journal-article","created":{"date-parts":[[2007,7,7]],"date-time":"2007-07-07T19:33:12Z","timestamp":1183836792000},"page":"89-98","source":"Crossref","is-referenced-by-count":0,"title":["Syllable recognition using integrated neural networks"],"prefix":"10.1002","volume":"21","author":[{"given":"Tatsuo","family":"Matsuoka","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroshi","family":"Hamada","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryohei","family":"Nakatsu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2007,3,22]]},"reference":[{"key":"e_1_2_1_2_2","unstructured":"T. K.Landauer C. A.Kamm andS.Singhal.Teaching a minimally structured back\u2010propagation network to recognize speech sounds. Proc. the 9th Annual Conference of the Cognitive Science Society pp.531\u2013536(1986)."},{"key":"e_1_2_1_3_2","first-page":"518","article-title":"Learning acoustic features from speech data using connectionist networks","volume":"2","author":"Watrous R. L.","year":"1986","journal-title":"Proc. Acoust. Soc., Japan"},{"key":"e_1_2_1_4_2","unstructured":"A.Waibel T.Hanazawa G.Hinton K.Shikano andK.Lang.Phoneme recognition: Neural networks vs. hidden Markov models. Proc. IEEE International Conference on Acoustics Speech and Signal Processing New York NY (Apr.1988)."},{"key":"e_1_2_1_5_2","article-title":"Dynamic neural network\u2014A new speech recognition model based on dynamic programming and neural network","volume":"87","author":"Sakoe H.","year":"1987","journal-title":"Trans. Committee on Speech Research, I.E.I.C.E."},{"key":"e_1_2_1_6_2","doi-asserted-by":"crossref","first-page":"318","DOI":"10.7551\/mitpress\/5236.001.0001","volume-title":"Parallel Distributed Processing","author":"Rumelhart D. E.","year":"1986"},{"key":"e_1_2_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/29.1643"},{"key":"e_1_2_1_8_2","doi-asserted-by":"crossref","unstructured":"T.IrinoandH.Kawahara.A study on the speaker\u2010independent feature extraction of Japanese vowels by neural networks. Presented at the 115th meeting of the Acoustical Society of America Seattle WA (May1988).","DOI":"10.1121\/1.2025394"},{"key":"e_1_2_1_9_2","article-title":"A study on syllable recognition using neural networks","volume":"3","author":"Matsuoka T.","year":"1988","journal-title":"Proc. ASJ Spring Meeting"},{"key":"e_1_2_1_10_2","article-title":"Syllable recognition using the integrated neural network","volume":"88","author":"Matsuoka T.","year":"1988","journal-title":"Trans. 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Committee on Speech Research, I.E.I.C.E."}],"container-title":["Systems and Computers in Japan"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fscj.4690210909","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/scj.4690210909","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,22]],"date-time":"2023-10-22T20:24:07Z","timestamp":1698006247000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/scj.4690210909"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1990,1]]},"references-count":12,"journal-issue":{"issue":"9","published-print":{"date-parts":[[1990,1]]}},"alternative-id":["10.1002\/scj.4690210909"],"URL":"https:\/\/doi.org\/10.1002\/scj.4690210909","archive":["Portico"],"relation":{},"ISSN":["0882-1666","1520-684X"],"issn-type":[{"value":"0882-1666","type":"print"},{"value":"1520-684X","type":"electronic"}],"subject":[],"published":{"date-parts":[[1990,1]]}}}