{"id":"https://openalex.org/W4283697392","doi":"https://doi.org/10.21437/interspeech.2022-886","title":"Transport-Oriented Feature Aggregation for Speaker Embedding Learning","display_name":"Transport-Oriented Feature Aggregation for Speaker Embedding Learning","publication_year":2022,"publication_date":"2022-09-16","ids":{"openalex":"https://openalex.org/W4283697392","doi":"https://doi.org/10.21437/interspeech.2022-886"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2022-886","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-886","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":"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/A5002748018","display_name":"Yusheng Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yusheng Tian","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100379862","display_name":"Jingyu Li","orcid":"https://orcid.org/0000-0001-9909-0277"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Li","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001795601","display_name":"Tan Lee","orcid":"https://orcid.org/0000-0002-7089-3436"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tan Lee","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002748018"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.1229,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.22148499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"316","last_page":"320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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":0.9995999932289124,"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/T11309","display_name":"Music and Audio Processing","score":0.9987999796867371,"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/computer-science","display_name":"Computer science","score":0.7608895301818848},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6841094493865967},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6274377107620239},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5100072622299194},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.507077693939209},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4065897464752197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7608895301818848},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6841094493865967},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6274377107620239},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5100072622299194},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.507077693939209},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4065897464752197},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2022-886","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2022-886","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/4","display_name":"Quality Education","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W385466589","https://openalex.org/W658020064","https://openalex.org/W2041823554","https://openalex.org/W2046056978","https://openalex.org/W2094100343","https://openalex.org/W2125101937","https://openalex.org/W2150769028","https://openalex.org/W2158131535","https://openalex.org/W2312355711","https://openalex.org/W2566365295","https://openalex.org/W2583638424","https://openalex.org/W2726515241","https://openalex.org/W2748488820","https://openalex.org/W2788357188","https://openalex.org/W2808631503","https://openalex.org/W2889519245","https://openalex.org/W2890964092","https://openalex.org/W2916104401","https://openalex.org/W2962832278","https://openalex.org/W2963371159","https://openalex.org/W2963420686","https://openalex.org/W2964201867","https://openalex.org/W2969810168","https://openalex.org/W2969985801","https://openalex.org/W2972369255","https://openalex.org/W2972756562","https://openalex.org/W3024869864","https://openalex.org/W3095476325","https://openalex.org/W3097152652","https://openalex.org/W3119577510","https://openalex.org/W3135006803","https://openalex.org/W3197392277","https://openalex.org/W4287753648","https://openalex.org/W4300614726","https://openalex.org/W4320869919"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2849310602","https://openalex.org/W2905271011","https://openalex.org/W2793270624","https://openalex.org/W3164948662","https://openalex.org/W4289536128","https://openalex.org/W3153597579","https://openalex.org/W4298151006"],"abstract_inverted_index":{"Pooling":[0],"is":[1,59,85],"needed":[2],"to":[3,38,61,88,92],"aggregate":[4],"frame-level":[5],"features":[6],"into":[7],"utterance-level":[8],"representations":[9],"for":[10,43],"speaker":[11,22,45,98],"modeling.Given":[12],"the":[13,28,32,50,54,72,94,101],"success":[14],"of":[15,53],"statistics-based":[16],"pooling":[17,108],"methods,":[18],"we":[19],"hypothesize":[20],"that":[21,66],"characteristics":[23],"are":[24],"well":[25],"represented":[26,70],"in":[27],"statistical":[29,75],"distribution":[30],"over":[31,106],"pre-aggregation":[33],"layer's":[34],"output,":[35],"and":[36,79,109],"propose":[37],"use":[39],"transport-oriented":[40],"feature":[41,56,83],"aggregation":[42,84],"deriving":[44],"embeddings.The":[46],"aggregated":[47],"representation":[48],"encodes":[49],"geometric":[51],"structure":[52],"underlying":[55],"distribution,":[57],"which":[58],"expected":[60],"contain":[62],"valuable":[63],"speaker-specific":[64],"information":[65],"may":[67],"not":[68],"be":[69],"by":[71],"commonly":[73],"used":[74],"measures":[76],"like":[77],"mean":[78],"variance.The":[80],"original":[81],"transportoriented":[82],"also":[86],"extended":[87],"a":[89],"weightedframe":[90],"version":[91],"incorporate":[93],"attention":[95],"mechanism.Experiments":[96],"on":[97],"verification":[99],"with":[100],"Voxceleb":[102],"dataset":[103],"show":[104],"improvement":[105],"statistics":[107],"its":[110],"attentive":[111],"variant.":[112]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}