{"id":"https://openalex.org/W2052687967","doi":"https://doi.org/10.1002/scj.4690190402","title":"Reduction of Word and Minimal Phrase Candidates for Speech Recognition Based on Phoneme Recognition","display_name":"Reduction of Word and Minimal Phrase Candidates for Speech Recognition Based on Phoneme Recognition","publication_year":1988,"publication_date":"1988-01-01","ids":{"openalex":"https://openalex.org/W2052687967","doi":"https://doi.org/10.1002/scj.4690190402","mag":"2052687967"},"language":"en","primary_location":{"id":"doi:10.1002/scj.4690190402","is_oa":false,"landing_page_url":"https://doi.org/10.1002/scj.4690190402","pdf_url":null,"source":{"id":"https://openalex.org/S58208175","display_name":"Systems and Computers in Japan","issn_l":"0882-1666","issn":["0882-1666","1520-684X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems and Computers in Japan","raw_type":"journal-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/A5108370359","display_name":"Shoichi Matsunaga","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Sho\u2010Ichi Matsunaga","raw_affiliation_strings":["NTT Electrical Communications Laboratories, Musashino, Japan 180","Sho-ichi Matsunaga graduated 1979 Dept. Inf. Eng., Fac. Eng., Kyushu Univ. Completed Master's program 1981 Grad. School, and affiliated with NTT. Engaged in research in speech recognition. Presently, Member of 4th Lab., Basic Inf. Corn. Div., NTT Basic Res. Lab., Member, Acoust. Soc. Jap"],"affiliations":[{"raw_affiliation_string":"NTT Electrical Communications Laboratories, Musashino, Japan 180","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"Sho-ichi Matsunaga graduated 1979 Dept. Inf. Eng., Fac. Eng., Kyushu Univ. Completed Master's program 1981 Grad. School, and affiliated with NTT. Engaged in research in speech recognition. Presently, Member of 4th Lab., Basic Inf. Corn. Div., NTT Basic Res. Lab., Member, Acoust. Soc. Jap","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105933825","display_name":"Masaki Kohda","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaki Kohda","raw_affiliation_strings":["Masaki Kohda graduated 1965 Dept. Electronic Eng., Fac. Eng., Nagoya Univ. Completed Master's program 1967 Grad. School, and affiliated with NTT. Engaged in researches in speech recognition, Presently, Chief Researcher, 4th. Lab., Basic Inf. Corn. Div., NTT Basic Res. Lab. Doctor of Eng. Member, Inf. Proc. Soc. Jap.; Acoust. Soc. Jap.; I.E.E.E.; and AVIRG","NTT Electrical Communications Laboratories, Musashino, Japan 180","Acoust. Soc. Jap","I.E.E.E","AVIRG","Masaki Kohda graduated 1965 Dept. Electronic Eng., Fac. Eng., Nagoya Univ. Completed Master's program 1967 Grad. School, and affiliated with NTT. Engaged in researches in speech recognition, Presently, Chief Researcher, 4th. Lab., Basic Inf. Corn. Div., NTT Basic Res. Lab. Doctor of Eng. Member, Inf. Proc. Soc. Jap"],"affiliations":[{"raw_affiliation_string":"Masaki Kohda graduated 1965 Dept. Electronic Eng., Fac. Eng., Nagoya Univ. Completed Master's program 1967 Grad. School, and affiliated with NTT. Engaged in researches in speech recognition, Presently, Chief Researcher, 4th. Lab., Basic Inf. Corn. Div., NTT Basic Res. Lab. Doctor of Eng. Member, Inf. Proc. Soc. Jap.; Acoust. Soc. Jap.; I.E.E.E.; and AVIRG","institution_ids":[]},{"raw_affiliation_string":"NTT Electrical Communications Laboratories, Musashino, Japan 180","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"Acoust. Soc. Jap","institution_ids":[]},{"raw_affiliation_string":"I.E.E.E","institution_ids":[]},{"raw_affiliation_string":"AVIRG","institution_ids":[]},{"raw_affiliation_string":"Masaki Kohda graduated 1965 Dept. Electronic Eng., Fac. Eng., Nagoya Univ. Completed Master's program 1967 Grad. School, and affiliated with NTT. Engaged in researches in speech recognition, Presently, Chief Researcher, 4th. Lab., Basic Inf. Corn. Div., NTT Basic Res. Lab. Doctor of Eng. Member, Inf. Proc. Soc. Jap","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108370359"],"corresponding_institution_ids":["https://openalex.org/I2251713219"],"apc_list":null,"apc_paid":null,"fwci":0.5534,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6729765,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"4","first_page":"11","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.996399998664856,"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"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.996399998664856,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9950000047683716,"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"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.993399977684021,"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/phrase","display_name":"Phrase","score":0.7833652496337891},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.777983546257019},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7572046518325806},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.596444845199585},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.5673345923423767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5498188138008118},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5482563972473145},{"id":"https://openalex.org/keywords/word-recognition","display_name":"Word recognition","score":0.5165897607803345},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5097524523735046},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.49890804290771484},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.47803816199302673},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4374052584171295},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1119336187839508},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07437014579772949}],"concepts":[{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.7833652496337891},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.777983546257019},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7572046518325806},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.596444845199585},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.5673345923423767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5498188138008118},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5482563972473145},{"id":"https://openalex.org/C150856459","wikidata":"https://www.wikidata.org/wiki/Q8034367","display_name":"Word recognition","level":3,"score":0.5165897607803345},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5097524523735046},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.49890804290771484},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.47803816199302673},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4374052584171295},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1119336187839508},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07437014579772949},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/scj.4690190402","is_oa":false,"landing_page_url":"https://doi.org/10.1002/scj.4690190402","pdf_url":null,"source":{"id":"https://openalex.org/S58208175","display_name":"Systems and Computers in Japan","issn_l":"0882-1666","issn":["0882-1666","1520-684X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems and Computers in Japan","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W1943381225","https://openalex.org/W2028088067","https://openalex.org/W2971021568"],"related_works":["https://openalex.org/W2039546652","https://openalex.org/W2944691285","https://openalex.org/W2401522294","https://openalex.org/W1962828410","https://openalex.org/W2253780618","https://openalex.org/W4205429340","https://openalex.org/W2601201456","https://openalex.org/W2079838398","https://openalex.org/W2158882055","https://openalex.org/W2136016133"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"paper":[2],"discusses":[3],"the":[4,13,21,27,34,43,46,49,55,58,63,69,73,84,92,100,103,106,113,117,124,136,144,147,164,169,179,185,191,198,202,204,207,215,219,228,247,257],"selection":[5,119,129,194,217],"of":[6,23,29,48,146,151,206,221],"candidates":[7,64,171,249],"in":[8,135,184,214,218],"speech":[9,30],"recognition":[10,25,107,139,181],"based":[11,19,224],"on":[12,20,225],"phoneme":[14,24,52,208],"recognition.":[15,126,200],"The":[16,127],"method":[17,101,120],"is":[18,36,82,109,121,130,195,212,231],"result":[22],"for":[26,32,71,91,143,237],"part":[28,70],"input,":[31],"which":[33,72],"segmentation":[35,74],"performed":[37,77,142,236],"with":[38,78,155,256],"a":[39,79,88,167,245],"high":[40,80],"reliability.":[41],"Using":[42],"information":[44,56],"concerning":[45,57],"order":[47],"phonemes":[50],"or":[51],"chains,":[53],"and":[54,60,96,223],"top":[59],"tail":[61],"phonemes,":[62],"are":[65],"selected.":[66],"Since":[67],"only":[68],"can":[75],"be":[76,210],"reliability":[81],"used,":[83],"candidate":[85,114,128,188,193,216,260],"reduction":[86],"has":[87,102],"great":[89],"effect":[90],"clearly":[93],"uttered":[94,159,240],"speech,":[95],"vice":[97],"versa.":[98],"Consequently,":[99],"feature":[104],"that":[105,226],"rate":[108],"degraded":[110],"less":[111],"by":[112,160,241],"selection.":[115,261],"First,":[116],"proposed":[118,192],"introduced":[122,196],"into":[123,197],"word":[125,148,170],"applied":[131],"to":[132,174,209,252],"all":[133],"words":[134],"dictionary.":[137],"A":[138],"experiment":[140,234],"was":[141,235],"cases":[145],"dictionary":[149],"composed":[150],"643":[152],"city":[153,157],"names,":[154],"100":[156],"names":[158],"50":[161],"examinees":[162],"as":[163,183],"input.":[165],"As":[166,244],"result,":[168,227,246],"were":[172,250],"reduced":[173,251],"16":[175],"percent,":[176,254],"maintaining":[177],"almost":[178],"same":[180],"performance":[182],"case":[186,258],"without":[187,259],"reduction.":[189],"Next,":[190],"phase":[199],"In":[201],"method,":[203],"location":[205],"rejected":[211],"estimated":[213],"derivation":[220],"hypothesis,":[222],"syntax":[229],"tree":[230],"back\u2010tracked.":[232],"An":[233],"235":[238],"phrases":[239],"2":[242],"examinees.":[243],"phrase":[248],"21":[253],"compared":[255]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}