{"id":"https://openalex.org/W49266694","doi":"https://doi.org/10.21437/interspeech.2006-216","title":"Phone recognition analysis for trajectory HMM","display_name":"Phone recognition analysis for trajectory HMM","publication_year":2006,"publication_date":"2006-09-17","ids":{"openalex":"https://openalex.org/W49266694","doi":"https://doi.org/10.21437/interspeech.2006-216","mag":"49266694"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2006-216","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2006-216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2006","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.pure.ed.ac.uk/ws/files/27377469/zhang_icslp2006.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100350631","display_name":"Le Zhang","orcid":"https://orcid.org/0000-0002-6930-8674"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Le Zhang","raw_affiliation_strings":["University of Edinburgh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027442277","display_name":"Steve Renals","orcid":"https://orcid.org/0000-0002-8790-3389"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steve Renals","raw_affiliation_strings":["School of Informatics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"paper 1203","last_page":"Mon3BuP.1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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/T10201","display_name":"Speech Recognition and Synthesis","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/T11309","display_name":"Music and Audio Processing","score":0.9988999962806702,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980000257492065,"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/trajectory","display_name":"Trajectory","score":0.8388130068778992},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.8116787672042847},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8115796446800232},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6016536355018616},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5958506464958191},{"id":"https://openalex.org/keywords/phone","display_name":"Phone","score":0.5411658883094788},{"id":"https://openalex.org/keywords/timit","display_name":"TIMIT","score":0.499453067779541},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4824869930744171},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43067994713783264},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4166123569011688},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.415658175945282},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3925062417984009},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09480023384094238},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07240307331085205}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8388130068778992},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8116787672042847},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8115796446800232},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6016536355018616},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5958506464958191},{"id":"https://openalex.org/C2778707766","wikidata":"https://www.wikidata.org/wiki/Q202064","display_name":"Phone","level":2,"score":0.5411658883094788},{"id":"https://openalex.org/C2778724510","wikidata":"https://www.wikidata.org/wiki/Q7670405","display_name":"TIMIT","level":3,"score":0.499453067779541},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4824869930744171},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43067994713783264},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4166123569011688},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.415658175945282},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3925062417984009},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09480023384094238},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07240307331085205},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/interspeech.2006-216","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2006-216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2006","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/f7bf55e5-7e63-4256-a91c-fde07d8f2214","is_oa":true,"landing_page_url":"http://www.isca-speech.org/archive/interspeech_2006/i06_1203.html","pdf_url":"https://www.pure.ed.ac.uk/ws/files/27377469/zhang_icslp2006.pdf","source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:pure.ed.ac.uk:publications/f7bf55e5-7e63-4256-a91c-fde07d8f2214","is_oa":true,"landing_page_url":"http://www.isca-speech.org/archive/interspeech_2006/i06_1203.html","pdf_url":"https://www.pure.ed.ac.uk/ws/files/27377469/zhang_icslp2006.pdf","source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W49266694.pdf","grobid_xml":"https://content.openalex.org/works/W49266694.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W7864212","https://openalex.org/W45652944","https://openalex.org/W1556556182","https://openalex.org/W1998362482","https://openalex.org/W2083393647","https://openalex.org/W2118825896","https://openalex.org/W2136652457","https://openalex.org/W2154920538"],"related_works":["https://openalex.org/W3134920593","https://openalex.org/W2153098279","https://openalex.org/W2143247386","https://openalex.org/W1990589093","https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W2501000458","https://openalex.org/W1578749070","https://openalex.org/W2146842779","https://openalex.org/W36113703"],"abstract_inverted_index":{"The":[0],"trajectory":[1,16,39,63,79],"HMM":[2],"has":[3],"been":[4],"shown":[5],"to":[6,76,94,116,127],"be":[7],"useful":[8],"for":[9],"model-based":[10],"speech":[11],"synthesis":[12],"where":[13],"a":[14,38,50,71,89,108],"smoothed":[15],"is":[17],"generated":[18],"using":[19,55],"temporal":[20,130],"constraints":[21,131],"imposed":[22],"by":[23,112],"dynamic":[24],"features.To":[25],"evaluate":[26],"the":[27,56,61],"performance":[28],"of":[29,69,110],"such":[30],"model":[31,129],"on":[32,42,49,103],"an":[33,96],"ASR":[34],"task,":[35],"we":[36],"present":[37],"decoder":[40],"based":[41],"tree":[43],"search":[44],"with":[45],"delayed":[46],"path":[47],"merging.Experiment":[48],"speaker-dependent":[51],"phone":[52],"recognition":[53],"task":[54],"MOCHA-TIMIT":[57],"database":[58],"shows":[59],"that":[60,98,125],"MLE-trained":[62],"model,":[64,74],"while":[65],"retaining":[66],"attractive":[67],"properties":[68],"being":[70,113],"proper":[72],"generative":[73],"tends":[75],"favour":[77],"over-smoothed":[78],"among":[80],"competing":[81],"hypothesises,":[82],"and":[83],"does":[84],"not":[85,133],"perform":[86],"better":[87,101],"than":[88],"conventional":[90],"HMM.We":[91],"use":[92],"this":[93],"build":[95],"argument":[97],"models":[99,124],"giving":[100],"fit":[102],"training":[104,117],"data":[105],"may":[106],"suffer":[107],"reduction":[109],"discrimination":[111],"too":[114],"faithful":[115],"data.This":[118],"partially":[119],"explains":[120],"why":[121],"alternative":[122],"acoustic":[123],"try":[126],"explicitly":[128],"do":[132],"achieve":[134],"significant":[135],"improvements":[136],"in":[137],"ASR.":[138]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
