{"id":"https://openalex.org/W4296068969","doi":"https://doi.org/10.21437/interspeech.2022-945","title":"ESSumm: Extractive Speech Summarization from Untranscribed Meeting","display_name":"ESSumm: Extractive Speech Summarization from Untranscribed Meeting","publication_year":2022,"publication_date":"2022-09-16","ids":{"openalex":"https://openalex.org/W4296068969","doi":"https://doi.org/10.21437/interspeech.2022-945"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2022-945","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-945","pdf_url":null,"source":{"id":"https://openalex.org/S4363604309","display_name":"Interspeech 2022","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2022","raw_type":"proceedings-article"},"type":"conference-paper","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/A5110195480","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0001-8932-6661"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jun Wang","raw_affiliation_strings":["University of Maryland, College Park, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5110195480"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.0122,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.78319851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3243","last_page":"3247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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":0.9998000264167786,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9990000128746033,"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/automatic-summarization","display_name":"Automatic summarization","score":0.9063766002655029},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7173710465431213},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5222995281219482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37158769369125366},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3697808086872101}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9063766002655029},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7173710465431213},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5222995281219482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37158769369125366},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3697808086872101}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2022-945","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-945","pdf_url":null,"source":{"id":"https://openalex.org/S4363604309","display_name":"Interspeech 2022","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W36558693","https://openalex.org/W1525595230","https://openalex.org/W1587353960","https://openalex.org/W1969700396","https://openalex.org/W1986304067","https://openalex.org/W2100355644","https://openalex.org/W2112107221","https://openalex.org/W2125336414","https://openalex.org/W2131124769","https://openalex.org/W2144211451","https://openalex.org/W2147574893","https://openalex.org/W2152789372","https://openalex.org/W2154652894","https://openalex.org/W2156411402","https://openalex.org/W2606974598","https://openalex.org/W2612675303","https://openalex.org/W2760577196","https://openalex.org/W2793429163","https://openalex.org/W2949530332","https://openalex.org/W2952138241","https://openalex.org/W2962704246","https://openalex.org/W2963108794","https://openalex.org/W2963929190","https://openalex.org/W2972388764","https://openalex.org/W3036601975","https://openalex.org/W3037217258","https://openalex.org/W3081312039","https://openalex.org/W3085629518","https://openalex.org/W3106234277","https://openalex.org/W3113822960","https://openalex.org/W3138773240","https://openalex.org/W3198084221","https://openalex.org/W3199088047","https://openalex.org/W4287989344","https://openalex.org/W4297809440"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W2351187795","https://openalex.org/W3204019825"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,31,73],"propose":[4],"a":[5,36,43,61,105],"novel":[6],"architecture":[7],"for":[8,68],"direct":[9,124],"extractive":[10],"speech-to-speech":[11],"summarization,":[12],"ESSumm,":[13],"which":[14],"is":[15,66,155],"an":[16],"unsupervised":[17,139],"model":[18],"without":[19,41],"dependence":[20],"on":[21,52,110,144],"intermediate":[22],"transcribed":[23],"text.Different":[24],"from":[25,39,87],"previous":[26],"methods":[27],"with":[28,104,132,146],"text":[29],"presentation,":[30],"are":[32,49],"aimed":[33],"at":[34],"generating":[35],"summary":[37,107],"directly":[38],"speech":[40,47,53,59,70,85,97,153],"transcription.First,":[42],"set":[44],"of":[45,96,122],"smaller":[46],"segments":[48,98],"extracted":[50],"based":[51],"signal's":[54],"acoustic":[55],"features.For":[56],"each":[57],"candidate":[58],"segment,":[60],"distance-based":[62],"summarization":[63,130,149],"confidence":[64],"score":[65],"designed":[67],"latent":[69],"representation":[71],"measure.Specifically,":[72],"leverage":[74],"the":[75,83,93,101,120,129],"off-the-shelf":[76],"self-supervised":[77],"convolutional":[78],"neural":[79],"network":[80],"to":[81,127],"extract":[82],"deep":[84],"features":[86],"raw":[88],"audio.Our":[89],"approach":[90],"automatically":[91],"predicts":[92],"optimal":[94],"sequence":[95],"that":[99,137],"capture":[100],"key":[102],"information":[103],"target":[106],"length.Extensive":[108],"results":[109],"two":[111],"well-known":[112],"meeting":[113],"datasets":[114],"(AMI":[115],"and":[116],"ICSI":[117],"corpora)":[118],"show":[119],"effectiveness":[121],"our":[123,138],"speech-based":[125,140],"method":[126,141],"improve":[128],"quality":[131],"untranscribed":[133],"data.We":[134],"also":[135],"observe":[136],"even":[142],"performs":[143],"par":[145],"recent":[147],"transcript-based":[148],"approaches,":[150],"where":[151],"extra":[152],"recognition":[154],"required.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}