{"id":"https://openalex.org/W2405455920","doi":"https://doi.org/10.21437/interspeech.2013-453","title":"Graph-based semi-supervised learning for phone and segment classification","display_name":"Graph-based semi-supervised learning for phone and segment classification","publication_year":2013,"publication_date":"2013-08-25","ids":{"openalex":"https://openalex.org/W2405455920","doi":"https://doi.org/10.21437/interspeech.2013-453","mag":"2405455920"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2013-453","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2013-453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2013","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/A5000919546","display_name":"Yuzong Liu","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"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuzong Liu","raw_affiliation_strings":["University of Washington ;"],"affiliations":[{"raw_affiliation_string":"University of Washington ;","institution_ids":["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":["University of Washington ;"],"affiliations":[{"raw_affiliation_string":"University of Washington ;","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000919546"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":3.4596,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.93241514,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.996399998664856,"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":0.9882000088691711,"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/timit","display_name":"TIMIT","score":0.8292320966720581},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7842110991477966},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.592158854007721},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5869351625442505},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5780020952224731},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5586291551589966},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5423321723937988},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5087423920631409},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4230627417564392},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4177822172641754},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21019181609153748},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.1372947096824646}],"concepts":[{"id":"https://openalex.org/C2778724510","wikidata":"https://www.wikidata.org/wiki/Q7670405","display_name":"TIMIT","level":3,"score":0.8292320966720581},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7842110991477966},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.592158854007721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5869351625442505},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5780020952224731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5586291551589966},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5423321723937988},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5087423920631409},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4230627417564392},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4177822172641754},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21019181609153748},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.1372947096824646}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2013-453","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2013-453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2013","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.475.4495","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.475.4495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ssli.ee.washington.edu/ssli/people/katrin/Papers/int13-gbl.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W137179480","https://openalex.org/W1552297528","https://openalex.org/W1630959083","https://openalex.org/W1998637406","https://openalex.org/W2047823992","https://openalex.org/W2073021346","https://openalex.org/W2077804127","https://openalex.org/W2109300274","https://openalex.org/W2120173366","https://openalex.org/W2132085065","https://openalex.org/W2136504847","https://openalex.org/W2166473218","https://openalex.org/W2397535009","https://openalex.org/W2400194987"],"related_works":["https://openalex.org/W80423236","https://openalex.org/W3164669818","https://openalex.org/W1573546415","https://openalex.org/W2906993205","https://openalex.org/W2094250226","https://openalex.org/W2608303656","https://openalex.org/W2098258572","https://openalex.org/W2167603772","https://openalex.org/W2624170553","https://openalex.org/W2074119280"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"several":[3],"novel":[4],"contributions":[5],"to":[6,22,27,75],"the":[7,28,65,79,85,94,105],"emerging":[8],"framework":[9],"of":[10,39,67],"graph-based":[11,20,45,68,95],"semi-supervised":[12],"learning":[13,21,80,107],"for":[14,55],"speech":[15],"processing.":[16],"First,":[17],"we":[18,42,48,71,102],"apply":[19],"variable-length":[23],"segments":[24],"rather":[25],"than":[26],"fixed-length":[29],"vector":[30],"representations":[31],"that":[32,59,93,104,111],"have":[33],"been":[34],"used":[35],"previously.":[36],"As":[37],"part":[38],"this":[40],"work":[41],"compare":[43],"various":[44],"learners,":[46],"and":[47,63,88],"utilize":[49],"an":[50],"efficient":[51],"feature":[52,57],"selection":[53],"technique":[54],"high-dimensional":[56],"spaces":[58],"alleviates":[60],"computational":[61],"costs":[62],"improves":[64],"per-formance":[66],"learners.":[69],"Finally,":[70],"present":[72],"a":[73],"method":[74],"improve":[76],"regularization":[77],"during":[78],"pro-cess.":[81],"Experimental":[82],"evaluation":[83],"on":[84],"TIMIT":[86],"frame":[87],"segment":[89],"classification":[90],"tasks":[91],"demonstrates":[92],"classifiers":[96],"outperform":[97],"standard":[98],"baseline":[99],"classifiers;":[100],"furthermore,":[101],"find":[103],"best":[106],"algorithms":[108],"are":[109],"those":[110],"can":[112],"incorporate":[113],"prior":[114],"knowledge.":[115],"1.":[116]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
