{"id":"https://openalex.org/W1998637406","doi":"https://doi.org/10.1109/asru.2007.4430138","title":"Graph-based learning for phonetic classification","display_name":"Graph-based learning for phonetic classification","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W1998637406","doi":"https://doi.org/10.1109/asru.2007.4430138","mag":"1998637406"},"language":"en","primary_location":{"id":"doi:10.1109/asru.2007.4430138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2007.4430138","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU)","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/A5097934309","display_name":"Andrie Alexandrescu","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrie Alexandrescu","raw_affiliation_strings":["Department of Computer Science, University of Washington, Seattle, WA, USA","University of Washington , Seattle"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"University of Washington , Seattle","institution_ids":["https://openalex.org/I58610484","https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050325468","display_name":"Katrin Kirchhoff","orcid":"https://orcid.org/0000-0002-6645-6030"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katrin Kirchhoff","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington, Seattle, WA, USA","University of Washington Department of Electrical Engineering, Seattle, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"University of Washington Department of Electrical Engineering, Seattle, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5097934309"],"corresponding_institution_ids":["https://openalex.org/I201448701","https://openalex.org/I58610484"],"apc_list":null,"apc_paid":null,"fwci":0.6334,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.67217818,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2","issue":null,"first_page":"359","last_page":"364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.7025332450866699},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6068598031997681},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5722540616989136},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5651304721832275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5521791577339172},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47729384899139404},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4534305930137634},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1826692819595337}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7025332450866699},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6068598031997681},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5722540616989136},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5651304721832275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5521791577339172},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47729384899139404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4534305930137634},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1826692819595337}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asru.2007.4430138","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2007.4430138","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7799999713897705,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W23846527","https://openalex.org/W91116557","https://openalex.org/W177307080","https://openalex.org/W811578723","https://openalex.org/W1497443639","https://openalex.org/W1515325541","https://openalex.org/W1585385982","https://openalex.org/W1630959083","https://openalex.org/W2037740282","https://openalex.org/W2061526129","https://openalex.org/W2071085454","https://openalex.org/W2100969003","https://openalex.org/W2104997912","https://openalex.org/W2111557120","https://openalex.org/W2122837498","https://openalex.org/W2127358574","https://openalex.org/W2131042651","https://openalex.org/W2229855789","https://openalex.org/W2401715402","https://openalex.org/W2404782708","https://openalex.org/W6607143959","https://openalex.org/W6635184699","https://openalex.org/W6636599907","https://openalex.org/W6675604347","https://openalex.org/W6676834449","https://openalex.org/W6712761716","https://openalex.org/W6712969915"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2513638114","https://openalex.org/W4390062853","https://openalex.org/W2340127552","https://openalex.org/W4389256085","https://openalex.org/W3210156800","https://openalex.org/W3033485676","https://openalex.org/W3166049060","https://openalex.org/W4311865232","https://openalex.org/W2904380457"],"abstract_inverted_index":{"We":[0,84],"introduce":[1],"graph-based":[2,8,91,109],"learning":[3,48,92,110],"for":[4],"acoustic-phonetic":[5],"classification.":[6],"In":[7],"learning,":[9],"training,":[10],"and":[11,96],"test":[12,35],"data":[13,82],"points":[14],"are":[15],"jointly":[16],"represented":[17],"in":[18,53],"a":[19,25,65,70,87,101],"wieghted":[20],"undirected":[21],"graph":[22],"characterized":[23],"by":[24,39,73],"weight":[26],"matrix":[27],"indicating":[28],"similarties":[29],"between":[30],"different":[31],"samples.":[32],"Classification":[33],"of":[34],"samples":[36],"is":[37,50],"achieved":[38],"label":[40],"propagation":[41],"over":[42,113],"the":[43,80],"entire":[44],"graph.":[45],"Although":[46],"this":[47],"technique":[49,88],"commnly":[51],"applied":[52],"semi-":[54],"supervised":[55,71],"settings,":[56],"we":[57],"show":[58,107],"how":[59],"it":[60],"can":[61],"also":[62,85],"be":[63],"as":[64],"post-":[66],"processing":[67],"step":[68],"to":[69,89,93],"classifier":[72],"imposing":[74],"additional":[75],"regularization":[76],"constraints":[77],"based":[78],"on":[79,100],"underlying":[81],"manifold.":[83],"present":[86],"adapt":[90],"large":[94],"datasets":[95],"evaluate":[97],"our":[98],"system":[99],"vowel":[102],"classification":[103],"task.":[104],"Our":[105],"results":[106],"that":[108],"improves":[111],"significantly":[112],"state-of-the-art":[114],"baselines.":[115]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}