{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T06:41:24Z","timestamp":1698043284852},"reference-count":9,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2007,3,21]],"date-time":"2007-03-21T00:00:00Z","timestamp":1174435200000},"content-version":"vor","delay-in-days":5923,"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":[[1991,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A new neural network and its learning algorithm are proposed. The neural network consists of four layers\u2014input, hidden, output and final output layers. The hidden and output layers are multiple. The proposed learning algorithm is called the SICL (spread pattern information and cooperative learning) method and has the following features: (1) the singular points of back propagation errors in the BP method are removed; (2) a spread pattern information (SI) algorithm is proposed; and (3) a cooperative learning (CL) algorithm is proposed.<\/jats:p><jats:p>Using the SICL method, it is possible to learn analog data accurately and to obtain a stable output. Using this neural network, the authors developed a speech production system consisting of a phonemic symbol production subsystem and a speech parameter production subsystem. The system is applied to speech data and the system performance is examined. Especially, for the speech parameter production subsystem, the learning capacity and the optimal area for learning constants are studied. As a result, it is shown that it is possible to learn and produce speech data with high accuracy using the proposed neural network.<\/jats:p>","DOI":"10.1002\/scj.4690220309","type":"journal-article","created":{"date-parts":[[2007,7,7]],"date-time":"2007-07-07T20:30:08Z","timestamp":1183840208000},"page":"82-93","source":"Crossref","is-referenced-by-count":0,"title":["Learning and production of speech pattern using multilayer neural networks"],"prefix":"10.1002","volume":"22","author":[{"given":"Mitsuo","family":"Komura","sequence":"first","affiliation":[]},{"given":"Akio","family":"Tanaka","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2007,3,21]]},"reference":[{"key":"e_1_2_1_2_2","first-page":"145","article-title":"Parallel networks that learn to pronounce English text","volume":"1","author":"Sejnowski T. J.","year":"1987","journal-title":"Comlex Systems"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/5236.001.0001"},{"key":"e_1_2_1_4_2","article-title":"Speech synthesis using neural network with cooperative learning mechanism","volume":"88","author":"Komura M.","year":"1988","journal-title":"I.E.I.C.E., Japan"},{"key":"e_1_2_1_5_2","unstructured":"F.ItakuraandS.Saito.Speech analysis\u2010synthesis system based on the partial autocorrelation coefficients. Acoustic Society of Japan Meeting (1969)."},{"key":"e_1_2_1_6_2","unstructured":"A.TanakaandM.Komura.Detection of Voiced\/Unvoiced Speech and Pitch Periods for Linear Prediction Vocoders. IIAS\u2010SIS Fujitsu Ltd. Research Report No. 36 (March1983)."},{"key":"e_1_2_1_7_2","unstructured":"M.KomuraandA.Tanaka.Speech analysis and synthesis based on linear prediction method\u2014Stability and source parameters extraction. Fujitsu IIAS\u2010SIS General Report No. 17 (May1988)."},{"key":"e_1_2_1_8_2","unstructured":"M.KomuraandA.Tanaka.Experimental analysis to learning and production of speech pattern using neural networks. I.E.I.C.E. Tech. Rep. SP88\u20108 (May1988)."},{"key":"e_1_2_1_9_2","unstructured":"A.TanakaandM.Komura.Theoretical and experimental analysis of a speech production system using neural networks. Papers of Technical Group on Pattern Recognition and Understanding. I.E.I.C.E. PRU88\u2010118 (Jan.1989) [in Japanese]."},{"key":"e_1_2_1_10_2","unstructured":"M.KomuraandA.Tanaka.Speech production using a neural network with a cooperative learning mechanism. IEEE Conference on Neural Information Processing Systems PI.25 Denver CO USA (Nov. 28\u2010Dec. 1 1988). Collected Papers of the Conference. Advances in Neural Information Processing System I. Morgan Kaufmann Publ. Inc. pp.232\u2013239(1989)."}],"container-title":["Systems and Computers in Japan"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fscj.4690220309","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/scj.4690220309","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,22]],"date-time":"2023-10-22T21:37:15Z","timestamp":1698010635000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/scj.4690220309"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1991,1]]},"references-count":9,"journal-issue":{"issue":"3","published-print":{"date-parts":[[1991,1]]}},"alternative-id":["10.1002\/scj.4690220309"],"URL":"https:\/\/doi.org\/10.1002\/scj.4690220309","archive":["Portico"],"relation":{},"ISSN":["0882-1666","1520-684X"],"issn-type":[{"value":"0882-1666","type":"print"},{"value":"1520-684X","type":"electronic"}],"subject":[],"published":{"date-parts":[[1991,1]]}}}