{"id":"https://openalex.org/W67810553","doi":"https://doi.org/10.21437/icslp.2000-444","title":"Broadcast news transcription in Mandarin","display_name":"Broadcast news transcription in Mandarin","publication_year":2000,"publication_date":"2000-10-16","ids":{"openalex":"https://openalex.org/W67810553","doi":"https://doi.org/10.21437/icslp.2000-444","mag":"67810553"},"language":"en","primary_location":{"id":"doi:10.21437/icslp.2000-444","is_oa":false,"landing_page_url":"https://doi.org/10.21437/icslp.2000-444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"6th International Conference on Spoken Language Processing (ICSLP 2000)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5070433127","display_name":"Langzhou Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Langzhou Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062446882","display_name":"Lori Lamel","orcid":"https://orcid.org/0000-0001-7443-9938"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lori Lamel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021094021","display_name":"Gilles Adda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gilles Adda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5109214406","display_name":"Jean\u2010Luc Gauvain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jean-Luc Gauvain","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1239,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.73979855,"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":"vol. 2, 1015","last_page":"1018"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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":0.9986000061035156,"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/T11309","display_name":"Music and Audio Processing","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/mandarin-chinese","display_name":"Mandarin Chinese","score":0.943697452545166},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7692302465438843},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.7104486227035522},{"id":"https://openalex.org/keywords/transcription","display_name":"Transcription (linguistics)","score":0.6753298044204712},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5534875988960266},{"id":"https://openalex.org/keywords/tone","display_name":"Tone (literature)","score":0.5469373464584351},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5399172306060791},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4986891746520996},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4543565511703491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4394102096557617},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.33018893003463745}],"concepts":[{"id":"https://openalex.org/C138954614","wikidata":"https://www.wikidata.org/wiki/Q9192","display_name":"Mandarin Chinese","level":2,"score":0.943697452545166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7692302465438843},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.7104486227035522},{"id":"https://openalex.org/C179926584","wikidata":"https://www.wikidata.org/wiki/Q207714","display_name":"Transcription (linguistics)","level":2,"score":0.6753298044204712},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5534875988960266},{"id":"https://openalex.org/C2780583480","wikidata":"https://www.wikidata.org/wiki/Q1366327","display_name":"Tone (literature)","level":2,"score":0.5469373464584351},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5399172306060791},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4986891746520996},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4543565511703491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4394102096557617},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.33018893003463745},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/icslp.2000-444","is_oa":false,"landing_page_url":"https://doi.org/10.21437/icslp.2000-444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"6th International Conference on Spoken Language Processing (ICSLP 2000)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.27.3214","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.27.3214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ftp://tlp.limsi.fr/public/icslp00_h4m.ps.Z","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W3765491","https://openalex.org/W5671660","https://openalex.org/W11920722","https://openalex.org/W82490022","https://openalex.org/W84827648","https://openalex.org/W265531733","https://openalex.org/W1522352264","https://openalex.org/W2146871184"],"related_works":["https://openalex.org/W2393887907","https://openalex.org/W2347443630","https://openalex.org/W2388826840","https://openalex.org/W2481138693","https://openalex.org/W2379831327","https://openalex.org/W2386691339","https://openalex.org/W156219719","https://openalex.org/W2365805939","https://openalex.org/W2287147624","https://openalex.org/W2163874654"],"abstract_inverted_index":{"In":[0,71],"this":[1,19],"paper,":[2],"our":[3],"work":[4,20],"in":[5,105],"developing":[6],"a":[7,22,96,110,129,136],"Mandarin":[8,36,66,82],"broadcast":[9,29,150],"news":[10,30],"transcription":[11,31,116],"system":[12,32,39],"is":[13,21,126,143],"described.":[14],"The":[15,38,51,115],"main":[16],"focus":[17],"of":[18,24,41,60,98,155],"port":[23],"the":[25,34,63,74,76,106,121,158],"LIMSI":[26],"American":[27],"English":[28],"to":[33,73],"Chinese":[35,83],"language.":[37],"consists":[40],"an":[42,46],"audio":[43],"partitioner":[44],"and":[45,102,108,135,148],"HMM-based":[47],"continuous":[48],"speech":[49,156],"recognizer.":[50],"acoustic":[52],"models":[53,78],"were":[54,79],"trained":[55,80],"on":[56,81,120],"about":[57,87],"24":[58],"hours":[59],"data":[61],"from":[62,157],"1997":[64,123],"Hub4":[65],"corpus":[67],"available":[68],"via":[69],"LDC.":[70],"addition":[72],"transcripts,":[75],"language":[77,113,138],"News":[84],"Corpus":[85],"containing":[86],"186":[88],"million":[89],"characters.":[90],"We":[91],"investigate":[92],"recognition":[93],"performance":[94],"as":[95],"function":[97],"lexical":[99],"size,":[100],"with":[101,109,131],"without":[103],"tone":[104,133],"lexicon,":[107],"topic":[111],"dependent":[112],"model.":[114,139],"character":[117],"error":[118],"rate":[119],"DARPA":[122],"test":[124],"set":[125],"18.1%":[127],"using":[128],"lexicon":[130],"3":[132],"levels":[134],"topic-based":[137],"1.":[140],"INTRODUCTION":[141],"It":[142],"well":[144],"known":[145],"that":[146],"radio":[147],"television":[149],"shows":[151],"contain":[152],"different":[153],"types":[154],"acoust...":[159]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}