{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T15:32:08Z","timestamp":1773156728329,"version":"3.50.1"},"reference-count":30,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2010,6,1]],"date-time":"2010-06-01T00:00:00Z","timestamp":1275350400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Transactions on Asian Language Information Processing"],"published-print":{"date-parts":[[2010,6]]},"abstract":"<jats:p>\n            Language models (LMs) are an important field of study in automatic speech recognition (ASR) systems. LM helps acoustic models find the corresponding word sequence of a given speech signal. Without it, ASR systems would not understand the language and it would be hard to find the correct word sequence. During the past few years, researchers have tried to incorporate long-range dependencies into statistical word-based\n            <jats:italic>n<\/jats:italic>\n            -gram LMs. One of these long-range dependencies is topic. Unlike words, topic is unobservable. Thus, it is required to find the meanings behind the words to get into the topic. This research is based on the belief that nouns contain topic information. We propose a new approach for a topic-dependent LM, where the topic is decided in an unsupervised manner. Latent Semantic Analysis (LSA) is employed to reveal hidden (latent) relations among nouns in the context words. To decide the topic of an event, a fixed size word history sequence (window) is observed, and voting is then carried out based on noun class occurrences weighted by a confidence measure. Experiments were conducted on an English corpus and a Japanese corpus:\n            <jats:italic>The Wall Street Journal<\/jats:italic>\n            corpus and\n            <jats:italic>Mainichi Shimbun<\/jats:italic>\n            (Japanese newspaper) corpus. The results show that our proposed method gives better perplexity than the comparative baselines, including a word-based\/class-based\n            <jats:italic>n<\/jats:italic>\n            -gram LM, their interpolated LM, a cache-based LM, a topic-dependent LM based on\n            <jats:italic>n<\/jats:italic>\n            -gram, and a topic-dependent LM based on Latent Dirichlet Allocation (LDA). The\n            <jats:italic>n<\/jats:italic>\n            -best list rescoring was conducted to validate its application in ASR systems.\n          <\/jats:p>","DOI":"10.1145\/1781134.1781137","type":"journal-article","created":{"date-parts":[[2010,6,11]],"date-time":"2010-06-11T18:52:51Z","timestamp":1276282371000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Topic-Dependent Language Model with Voting on Noun History"],"prefix":"10.1145","volume":"9","author":[{"given":"Welly","family":"Naptali","sequence":"first","affiliation":[{"name":"Toyohashi University of Technology"}]},{"given":"Masatoshi","family":"Tsuchiya","sequence":"additional","affiliation":[{"name":"Toyohashi University of Technology"}]},{"given":"Seiichi","family":"Nakagawa","sequence":"additional","affiliation":[{"name":"Toyohashi University of Technology"}]}],"member":"320","published-online":{"date-parts":[[2010,6]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/89.709671"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.1996.540318"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.3115\/1073483.1073485"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/944919.944937"},{"key":"e_1_2_1_5_1","volume-title":"Proceedings of the European Conference on Speech Communication and Technology (INTERSPEECH\u201905)","author":"Broman S."},{"key":"e_1_2_1_6_1","first-page":"18","article-title":"Class-based n-gram models of natural language","volume":"18","author":"Brown P. F.","year":"1990","journal-title":"Comput. Linguist."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1482343.1482345"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.3115\/976973.977012"},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Dhillon I. S. Fan J. and Guan Y. 2001. Efficient clustering of very large document collections. Data Mining for Scientific and Engineering Applications V. K. R. Grossman C. Kamath and R. Namburu eds. Kluwer Academic Publishers 357--381. Dhillon I. S. Fan J. and Guan Y. 2001. Efficient clustering of very large document collections. Data Mining for Scientific and Engineering Applications V. K. R. Grossman C. Kamath and R. Namburu eds. Kluwer Academic Publishers 357--381.","DOI":"10.1007\/978-1-4615-1733-7_20"},{"key":"e_1_2_1_10_1","volume-title":"Proceedings of the International Conference on Speech Communication and Technology (EUROSPEECH\u201999)","author":"Gildea D."},{"key":"e_1_2_1_11_1","volume-title":"Proceedings of the Uncertainty in Artificial Intelligence (UAI\u201999)","author":"Hofmann T.","year":"1999"},{"key":"e_1_2_1_12_1","article-title":"Modeling long distance dependence in language: Topic mixtures vs. dynamic cache models","author":"Iyer R.","year":"1996","journal-title":"IEEE Trans. Speech Audio Proc. 236--239."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3115\/1075812.1075828"},{"key":"e_1_2_1_14_1","volume-title":"Proceedings of the Workshop on Pattern Recognition in Practice (WPPP\u201980)","author":"Jelinek F."},{"key":"e_1_2_1_15_1","first-page":"275","article-title":"Comparison of dimension reduction methods for automated essay grading","volume":"11","author":"Kakkonen T.","year":"2008","journal-title":"Educ. Tech. Soc."},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-6393(01)00041-3"},{"key":"e_1_2_1_17_1","volume-title":"Proceedings of the European Conference on Speech Communication and Technology (EUROSPEECH\u201993)","author":"Kneser R."},{"key":"e_1_2_1_18_1","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP\u201993)","author":"Kneser R."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.56193"},{"key":"e_1_2_1_20_1","volume-title":"Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (ACL\u201907)","author":"Liu F."},{"key":"e_1_2_1_21_1","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP\u201908)","author":"Liu Y."},{"key":"e_1_2_1_22_1","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP\u201992)","author":"Nakagawa S."},{"key":"e_1_2_1_23_1","first-page":"85","article-title":"Word co-occurrence matrix and context dependent class in lsa based language model for speech recognition","volume":"3","author":"Naptali W.","year":"2009","journal-title":"North Atlantic Univ. Union Inter. J. Comput."},{"key":"e_1_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Rosenfeld R. 1996. A maximum entropy approach to additive statistical language modeling. Comput. Speech Lang. Rosenfeld R. 1996. A maximum entropy approach to additive statistical language modeling. Comput. Speech Lang.","DOI":"10.1006\/csla.1996.0011"},{"key":"e_1_2_1_25_1","volume-title":"Proceedings of the International Conference on New Methods in Language Processing (ICNMLP\u201994)","author":"Schmid H.","year":"1994"},{"key":"e_1_2_1_26_1","volume-title":"Proceedings of the International Conference on Spoken Language Processing (ICSLP\u201902)","author":"Stolcke A.","year":"2002"},{"key":"e_1_2_1_27_1","volume-title":"Proceedings of the International Conference on Spoken Language Processing (ICSLP\u201900)","author":"Strik H."},{"key":"e_1_2_1_28_1","volume-title":"Proceedings of the European Conference on Speech Communication and Technology (EUROSPEECH\u201901)","author":"Strik H.","year":"2091"},{"key":"e_1_2_1_29_1","unstructured":"Yung S. Evermann G. Gales M. Hain T. Kershaw D. Moore G. Odell J. Ollason D. Povey D. Valtchev V. and Woodland P. 2005. The HTK Book (for HTK version 3.3). Cambridge. Yung S. Evermann G. Gales M. Hain T. Kershaw D. Moore G. Odell J. Ollason D. Povey D. Valtchev V. and Woodland P. 2005. The HTK Book (for HTK version 3.3) . Cambridge."},{"key":"e_1_2_1_30_1","volume-title":"Proceedings of the Asian Workshop on Speech Science and Technology (SP\u201908)","author":"Zhang J."}],"container-title":["ACM Transactions on Asian Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1781134.1781137","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1781134.1781137","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T11:39:48Z","timestamp":1750246788000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1781134.1781137"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,6]]},"references-count":30,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2010,6]]}},"alternative-id":["10.1145\/1781134.1781137"],"URL":"https:\/\/doi.org\/10.1145\/1781134.1781137","relation":{},"ISSN":["1530-0226","1558-3430"],"issn-type":[{"value":"1530-0226","type":"print"},{"value":"1558-3430","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,6]]},"assertion":[{"value":"2009-07-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2010-02-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2010-06-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}