{"id":"https://openalex.org/W8053366","doi":"https://doi.org/10.21437/interspeech.2010-514","title":"Within and across sentence boundary language model","display_name":"Within and across sentence boundary language model","publication_year":2010,"publication_date":"2010-09-26","ids":{"openalex":"https://openalex.org/W8053366","doi":"https://doi.org/10.21437/interspeech.2010-514","mag":"8053366"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2010-514","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2010","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015201403","display_name":"Saeedeh Momtazi","orcid":"https://orcid.org/0000-0002-8110-1342"},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Saeedeh Momtazi","raw_affiliation_strings":["Saarland University, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Saarland University, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I91712215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051588436","display_name":"Friedrich Faubel","orcid":null},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Friedrich Faubel","raw_affiliation_strings":["Saarland University, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Saarland University, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I91712215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008875255","display_name":"Dietrich Klakow","orcid":"https://orcid.org/0000-0002-4147-9690"},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dietrich Klakow","raw_affiliation_strings":["saarland university"],"affiliations":[{"raw_affiliation_string":"saarland university","institution_ids":["https://openalex.org/I91712215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015201403"],"corresponding_institution_ids":["https://openalex.org/I91712215"],"apc_list":null,"apc_paid":null,"fwci":2.3274,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.88799262,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1800","last_page":"1803"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trigram","display_name":"Trigram","score":0.9582323431968689},{"id":"https://openalex.org/keywords/perplexity","display_name":"Perplexity","score":0.9516186714172363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7432622909545898},{"id":"https://openalex.org/keywords/treebank","display_name":"Treebank","score":0.7119731307029724},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.7097245454788208},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6572920680046082},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6197654604911804},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5816284418106079},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5422876477241516},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5167838335037231},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.43039047718048096},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34781333804130554},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18510043621063232},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.06972217559814453}],"concepts":[{"id":"https://openalex.org/C137546455","wikidata":"https://www.wikidata.org/wiki/Q3213474","display_name":"Trigram","level":2,"score":0.9582323431968689},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.9516186714172363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7432622909545898},{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.7119731307029724},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7097245454788208},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6572920680046082},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6197654604911804},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5816284418106079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5422876477241516},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5167838335037231},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.43039047718048096},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34781333804130554},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18510043621063232},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.06972217559814453},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2010-514","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-514","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2010","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.176.7617","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.176.7617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.lsv.uni-saarland.de/personalPages/smomtazi/papers/SaeedehMomtazi-INTERSPEECH10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W98731357","https://openalex.org/W155299729","https://openalex.org/W1631260214","https://openalex.org/W1632114991","https://openalex.org/W2121227244","https://openalex.org/W2123893795","https://openalex.org/W2949237929","https://openalex.org/W3021713638"],"related_works":["https://openalex.org/W2105076537","https://openalex.org/W2020757772","https://openalex.org/W2041167939","https://openalex.org/W2551914602","https://openalex.org/W1620568205","https://openalex.org/W2964047924","https://openalex.org/W2950575438","https://openalex.org/W2053242504","https://openalex.org/W79835312","https://openalex.org/W2123893795"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"two":[5],"different":[6],"language":[7,144],"modeling":[8],"approaches,":[9],"namely":[10],"skip":[11,24,130],"trigram":[12,25,42,131],"and":[13,78,97,109,113,123,132],"across":[14,51,133],"sentence":[15,52,134],"boundary,":[16],"to":[17,29,39,63],"capture":[18],"the":[19,35,40,44,56,60,65,72,76,79,86,103,107,110,121,124,128,141,152],"long":[20],"range":[21],"dependencies.":[22],"The":[23,50,117],"model":[26,54,81,145],"is":[27,48,69],"able":[28],"cover":[30],"more":[31],"predecessor":[32],"words":[33],"of":[34,59,93,120,149],"present":[36],"word":[37,57,77,108,122],"compared":[38],"normal":[41],"while":[43,140],"same":[45,153],"memory":[46],"space":[47],"required.":[49],"boundary":[53,135],"uses":[55],"distribution":[58],"previous":[61],"sentences":[62],"calculate":[64],"unigram":[66],"probability":[67,74],"which":[68],"applied":[70],"as":[71],"emission":[73],"in":[75],"class":[80,111,125],"frameworks.":[82],"Our":[83],"experiments":[84],"on":[85,151],"Penn":[87],"Treebank":[88],"[1]":[89],"show":[90],"that":[91],"each":[92],"our":[94],"proposed":[95,129],"models":[96,112,126,136],"also":[98],"their":[99,114],"combination":[100],"significantly":[101],"outperform":[102],"baseline":[104],"for":[105],"both":[106],"linear":[115,118],"interpolation.":[116],"interpolation":[119],"with":[127],"achieves":[137],"118.4":[138],"perplexity":[139,148],"best":[142],"state-of-the-art":[143],"has":[146],"a":[147],"137.2":[150],"dataset.":[154],"1.":[155]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}