{"id":"https://openalex.org/W2128297470","doi":"https://doi.org/10.1109/slt.2010.5700881","title":"Call transcript segmentation using word cooccurrence model","display_name":"Call transcript segmentation using word cooccurrence model","publication_year":2010,"publication_date":"2010-12-01","ids":{"openalex":"https://openalex.org/W2128297470","doi":"https://doi.org/10.1109/slt.2010.5700881","mag":"2128297470"},"language":"en","primary_location":{"id":"doi:10.1109/slt.2010.5700881","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt.2010.5700881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Spoken Language Technology Workshop","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/A5053319645","display_name":"Shajith Ikbal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Shajith Ikbal","raw_affiliation_strings":["IBM Research, Bangalore, India","IBM Research. Bangalore, India"],"affiliations":[{"raw_affiliation_string":"IBM Research, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research. Bangalore, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045869355","display_name":"Karthik Visweswariah","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Karthik Visweswariah","raw_affiliation_strings":["IBM Research, Bangalore, India","IBM Research. Bangalore, India"],"affiliations":[{"raw_affiliation_string":"IBM Research, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research. Bangalore, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053319645"],"corresponding_institution_ids":["https://openalex.org/I4210103279"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13982711,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":null,"first_page":"372","last_page":"377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","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/T12031","display_name":"Speech and dialogue systems","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9995999932289124,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9994000196456909,"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":0.82036292552948},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7560304999351501},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.7015888690948486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6512374877929688},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5849045515060425},{"id":"https://openalex.org/keywords/cohesion","display_name":"Cohesion (chemistry)","score":0.5187163949012756},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4942207634449005},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.4402596354484558},{"id":"https://openalex.org/keywords/speech-segmentation","display_name":"Speech segmentation","score":0.4284592270851135},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3921649754047394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.82036292552948},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7560304999351501},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7015888690948486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6512374877929688},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5849045515060425},{"id":"https://openalex.org/C104054115","wikidata":"https://www.wikidata.org/wiki/Q216828","display_name":"Cohesion (chemistry)","level":2,"score":0.5187163949012756},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4942207634449005},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.4402596354484558},{"id":"https://openalex.org/C207030507","wikidata":"https://www.wikidata.org/wiki/Q2266173","display_name":"Speech segmentation","level":3,"score":0.4284592270851135},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3921649754047394},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/slt.2010.5700881","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt.2010.5700881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Spoken Language Technology Workshop","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W94155879","https://openalex.org/W1534730506","https://openalex.org/W1557074680","https://openalex.org/W1593045043","https://openalex.org/W1604285433","https://openalex.org/W1710422233","https://openalex.org/W1828401780","https://openalex.org/W2014116493","https://openalex.org/W2015933299","https://openalex.org/W2027823133","https://openalex.org/W2098162425","https://openalex.org/W2100322480","https://openalex.org/W2135909747","https://openalex.org/W2138309071","https://openalex.org/W2139193890","https://openalex.org/W2140836433","https://openalex.org/W2147880316","https://openalex.org/W2148818577","https://openalex.org/W2949693768","https://openalex.org/W6603892199","https://openalex.org/W6631918358","https://openalex.org/W6635456232","https://openalex.org/W6637782871","https://openalex.org/W6638575021","https://openalex.org/W6653780602","https://openalex.org/W6675415716","https://openalex.org/W6680779052","https://openalex.org/W6682082992"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2114846443","https://openalex.org/W2093471820","https://openalex.org/W3102147106","https://openalex.org/W2347460059","https://openalex.org/W50079190","https://openalex.org/W3136048405","https://openalex.org/W182104056","https://openalex.org/W3143595119","https://openalex.org/W2208878950"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4,72],"a":[5],"word":[6,93,101,129],"cooccurrence":[7,94,102,130],"model":[8,19,45,103,131],"to":[9,25,35,87,104],"perform":[10,88],"topic":[11,39,134],"segmentation":[12,89,135],"of":[13,32,50,58,67,75,119,128],"call":[14,69],"center":[15],"conversational":[16],"speech.":[17],"This":[18],"is":[20],"estimated":[21],"from":[22],"training":[23],"data":[24],"discriminatively":[26],"represent":[27],"how":[28],"likely":[29],"various":[30,65],"pairs":[31],"words":[33],"are":[34],"cooccur":[36],"within":[37],"homogeneous":[38],"segments.":[40],"We":[41,71],"show":[42,125],"that":[43],"such":[44,77],"provide":[46,55],"an":[47],"effective":[48],"measure":[49],"lexical":[51],"cohesion":[52],"and":[53],"hence":[54],"useful":[56],"evidence":[57,78],"topical":[59],"coherence":[60],"or":[61],"lack":[62],"thereof":[63],"between":[64],"parts":[66],"the":[68,92,126,133],"transcripts.":[70],"two":[73],"approaches":[74,121,124],"utilizing":[76,91],"for":[79,132],"segmentation:":[80],"1)":[81],"An":[82],"efficient":[83],"dynamic":[84],"programming":[85],"algorithm":[86],"simply":[90],"model.":[95],"2)":[96],"Extracting":[97],"features":[98,109],"based":[99,115],"on":[100],"utilize":[105],"them":[106],"as":[107],"additional":[108],"in":[110],"conditional":[111],"random":[112],"field":[113],"(CRF)":[114],"segmentation.":[116],"Experimental":[117],"evaluation":[118],"these":[120],"against":[122],"state-of-the-art":[123],"effectiveness":[127],"task.":[136]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}