{"id":"https://openalex.org/W2889070349","doi":"https://doi.org/10.21437/interspeech.2018-1375","title":"Prediction of Subjective Listening Effort from Acoustic Data with Non-Intrusive Deep Models","display_name":"Prediction of Subjective Listening Effort from Acoustic Data with Non-Intrusive Deep Models","publication_year":2018,"publication_date":"2018-08-28","ids":{"openalex":"https://openalex.org/W2889070349","doi":"https://doi.org/10.21437/interspeech.2018-1375","mag":"2889070349"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2018-1375","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2018-1375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2018","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://publica.fraunhofer.de/documents/N-581823.html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059371151","display_name":"Paul Kranzusch","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Paul Kranzusch","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080820413","display_name":"Rainer H\u00fcber","orcid":"https://orcid.org/0000-0001-7241-2037"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rainer Huber","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083361590","display_name":"Melanie Kr\u00fcger","orcid":"https://orcid.org/0000-0001-5344-5060"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Melanie Kr\u00fcger","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076869895","display_name":"Birger Kollmeier","orcid":"https://orcid.org/0000-0001-8584-4779"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Birger Kollmeier","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067491941","display_name":"Bernd T. Meyer","orcid":"https://orcid.org/0000-0001-9190-2111"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bernd T. Meyer","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059371151"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1651,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.44599881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"981","last_page":"985"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9848999977111816,"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":0.9848999977111816,"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":0.9013000130653381,"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/active-listening","display_name":"Active listening","score":0.6869242787361145},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6740162968635559},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5048354268074036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3665512204170227},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13730934262275696}],"concepts":[{"id":"https://openalex.org/C177291462","wikidata":"https://www.wikidata.org/wiki/Q423038","display_name":"Active listening","level":2,"score":0.6869242787361145},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6740162968635559},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5048354268074036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3665512204170227},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13730934262275696},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.21437/interspeech.2018-1375","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2018-1375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2018","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-581823","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-581823.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IDMT","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/407530","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/407530","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:fraunhofer.de:N-581823","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-581823.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IDMT","raw_type":"Conference Paper"},"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2317723112","https://openalex.org/W2475724061","https://openalex.org/W2773393136","https://openalex.org/W2174706483","https://openalex.org/W2997121352","https://openalex.org/W419536403","https://openalex.org/W2506280730","https://openalex.org/W4237969969"],"abstract_inverted_index":{"The":[0],"effort":[1,80],"of":[2,16,88,113,124,138,150],"listening":[3,79],"to":[4,121],"spoken":[5],"language":[6],"is":[7,68],"a":[8,28,38,96,136],"highly":[9],"important":[10],"perceptive":[11],"measure":[12],"for":[13,48,94],"the":[14,32,109,117],"design":[15],"speech":[17,50,99],"enhancement":[18,143],"algorithms":[19],"and":[20,58,119,126,141,152],"hearing-aid":[21],"processing.":[22],"In":[23],"previous":[24],"research,":[25],"we":[26],"proposed":[27],"model":[29,59],"that":[30,134],"quantifies":[31],"phoneme":[33,114],"output":[34,60],"probabilities":[35],"obtained":[36],"from":[37,116],"deep":[39],"neural":[40],"net":[41],"(DNN),":[42],"which":[43,67],"resulted":[44],"in":[45,63,72,82,131,157],"accurate":[46],"predictions":[47,104],"unseen":[49,83],"samples.":[51],"However,":[52],"high":[53],"correlations":[54],"between":[55],"subjective":[56,122],"ratings":[57,123],"were":[61],"observed":[62],"known":[64],"noise":[65,90,139],"types,":[66],"an":[69,147],"unrealistic":[70],"assumption":[71],"real-life":[73],"scenarios.":[74],"This":[75],"paper":[76],"explores":[77],"non-intrusive":[78],"prediction":[81],"noisy":[84],"environments.":[85],"A":[86],"set":[87],"different":[89],"types":[91,140],"are":[92,105],"used":[93],"training":[95],"standard":[97],"automatic":[98],"recognition":[100],"(ASR)":[101],"system.":[102],"Model":[103],"produced":[106],"by":[107],"measuring":[108],"mean":[110],"temporal":[111],"distance":[112],"vectors":[115],"DNN":[118],"compared":[120],"hearing-impaired":[125],"normal-hearing":[127],"listener":[128],"responses":[129],"group":[130],"three":[132,154],"databases":[133],"cover":[135],"variety":[137],"signal":[142],"algorithms.":[144],"We":[145],"obtain":[146],"average":[148],"correlation":[149],"0.88":[151],"outperform":[153],"baseline":[155],"measures":[156],"most":[158],"conditions.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
