{"id":"https://openalex.org/W206810795","doi":"https://doi.org/10.21437/interspeech.2008-244","title":"Getting the last laugh: automatic laughter segmentation in meetings","display_name":"Getting the last laugh: automatic laughter segmentation in meetings","publication_year":2008,"publication_date":"2008-09-22","ids":{"openalex":"https://openalex.org/W206810795","doi":"https://doi.org/10.21437/interspeech.2008-244","mag":"206810795"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2008-244","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2008-244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2008","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/A5059962618","display_name":"Mary Tai Knox","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mary Tai Knox","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112003894","display_name":"Nelson Morgan","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nelson Morgan","raw_affiliation_strings":["University of California, Berkeley, Berkeley, United States"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, United States","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061251853","display_name":"Nikki Mirghafori","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikki Mirghafori","raw_affiliation_strings":["University of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059962618"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.1484,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.94829947,"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":"797","last_page":"800"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9929999709129333,"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":0.9929999709129333,"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/T10860","display_name":"Speech and Audio Processing","score":0.9833999872207642,"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/T11439","display_name":"Video Analysis and Summarization","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8109506368637085},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.759040355682373},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.7470086812973022},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6653878092765808},{"id":"https://openalex.org/keywords/viterbi-decoder","display_name":"Viterbi decoder","score":0.642504096031189},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6378812789916992},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6371350884437561},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.574815034866333},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5537779331207275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5412821769714355},{"id":"https://openalex.org/keywords/laughter","display_name":"Laughter","score":0.52912437915802},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.527839183807373},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49918150901794434},{"id":"https://openalex.org/keywords/recall-rate","display_name":"Recall rate","score":0.45163896679878235},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4356098175048828},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.43306174874305725},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10661560297012329},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07379251718521118}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8109506368637085},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.759040355682373},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.7470086812973022},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6653878092765808},{"id":"https://openalex.org/C117379686","wikidata":"https://www.wikidata.org/wiki/Q6996459","display_name":"Viterbi decoder","level":3,"score":0.642504096031189},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6378812789916992},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6371350884437561},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.574815034866333},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5537779331207275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5412821769714355},{"id":"https://openalex.org/C2780775679","wikidata":"https://www.wikidata.org/wiki/Q170579","display_name":"Laughter","level":2,"score":0.52912437915802},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.527839183807373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49918150901794434},{"id":"https://openalex.org/C2987098735","wikidata":"https://www.wikidata.org/wiki/Q3808900","display_name":"Recall rate","level":2,"score":0.45163896679878235},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4356098175048828},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.43306174874305725},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10661560297012329},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07379251718521118},{"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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2008-244","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2008-244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2008","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4099999964237213,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W27690075","https://openalex.org/W152150158","https://openalex.org/W1520297327","https://openalex.org/W1553004968","https://openalex.org/W1562563659","https://openalex.org/W1591607137","https://openalex.org/W1591747970","https://openalex.org/W1969761120","https://openalex.org/W1992272902","https://openalex.org/W2097560587","https://openalex.org/W2124000984","https://openalex.org/W2140035970","https://openalex.org/W2169264834","https://openalex.org/W3216401400","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2102309991","https://openalex.org/W1795315578","https://openalex.org/W2373954783","https://openalex.org/W2535886977","https://openalex.org/W2133857928","https://openalex.org/W2143297499","https://openalex.org/W2356694334","https://openalex.org/W2991144886","https://openalex.org/W2790444905","https://openalex.org/W1843778016"],"abstract_inverted_index":{"Our":[0,22],"goal":[1],"in":[2],"this":[3],"work":[4,24],"was":[5],"to":[6,11,27,86,148],"develop":[7],"an":[8,97],"accurate":[9],"method":[10],"identify":[12],"laughter":[13,33,139],"segments,":[14],"ultimately":[15],"for":[16],"the":[17,77,110,136,143],"purpose":[18],"of":[19,32],"speaker":[20],"recognition.":[21],"previous":[23,54],"used":[25,101],"MLPs":[26],"perform":[28],"frame":[29],"level":[30],"detection":[31,140],"using":[34],"short-term":[35],"features,":[36,61],"including":[37,57,76],"MFCCs":[38],"and":[39,41,59,64,80,93,114,123],"pitch,":[40],"achieved":[42],"a":[43,68,119],"7.9%":[44],"EER":[45,88,95],"on":[46,89,96,127,142],"our":[47,53,83,90,128,132],"test":[48,91,99,129],"set.":[49,130],"We":[50],"improved":[51,85],"upon":[52],"results":[55,84,107,141],"by":[56,102,108],"high-level":[58],"long-term":[60,78],"median":[62,81],"filtering,":[63,82],"performing":[65],"segmentation":[66,106],"via":[67],"hybrid":[69,111],"MLP/HMM":[70,112],"system":[71,113],"with":[72],"Viterbi":[73,115],"decoding.":[74],"Upon":[75],"features":[79],"5.4%":[87],"set":[92,100],"2.7%":[94],"equal-prior":[98],"others.":[103],"After":[104],"attaining":[105],"incorporating":[109],"decoding,":[116],"we":[117],"had":[118],"78.5%":[120],"precision":[121],"rate":[122,126],"85.3%":[124],"recall":[125],"To":[131],"knowledge":[133],"these":[134],"are":[135],"best":[137],"known":[138],"ICSI":[144],"Meeting":[145],"Recorder":[146],"Corpus":[147],"date.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
