{"id":"https://openalex.org/W2978824373","doi":"https://doi.org/10.1080/0952813x.2019.1672795","title":"An emergent deep developmental model for auditory learning","display_name":"An emergent deep developmental model for auditory learning","publication_year":2019,"publication_date":"2019-10-03","ids":{"openalex":"https://openalex.org/W2978824373","doi":"https://doi.org/10.1080/0952813x.2019.1672795","mag":"2978824373"},"language":"en","primary_location":{"id":"doi:10.1080/0952813x.2019.1672795","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2019.1672795","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental & Theoretical Artificial Intelligence","raw_type":"journal-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/A5003077831","display_name":"Dongshu Wang","orcid":"https://orcid.org/0000-0003-3145-4956"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongshu Wang","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, PR China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112840893","display_name":"Yadong Zhang","orcid":"https://orcid.org/0000-0002-9716-4663"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yadong Zhang","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, PR China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042584819","display_name":"Jianbin Xin","orcid":"https://orcid.org/0000-0002-1024-4135"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianbin Xin","raw_affiliation_strings":["School of Electrical Engineering, Zhengzhou University, Zhengzhou, PR China"],"raw_orcid":"https://orcid.org/0000-0002-1024-4135","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou, PR China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042584819"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.10636225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"32","issue":"4","first_page":"665","last_page":"684"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9886999726295471,"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":0.9886999726295471,"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/T10320","display_name":"Neural Networks and Applications","score":0.9804999828338623,"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":0.9758999943733215,"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":0.85811448097229},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6300760507583618},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5538387298583984},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5470420718193054},{"id":"https://openalex.org/keywords/auditory-system","display_name":"Auditory system","score":0.5363306999206543},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4751971960067749},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4624066650867462},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.17586255073547363},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.08977976441383362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.85811448097229},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6300760507583618},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5538387298583984},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5470420718193054},{"id":"https://openalex.org/C2777443451","wikidata":"https://www.wikidata.org/wiki/Q821413","display_name":"Auditory system","level":2,"score":0.5363306999206543},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4751971960067749},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4624066650867462},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.17586255073547363},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.08977976441383362},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/0952813x.2019.1672795","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2019.1672795","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental & Theoretical Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5899999737739563,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1496101456","https://openalex.org/W1566152429","https://openalex.org/W1975399530","https://openalex.org/W1988812422","https://openalex.org/W1988878611","https://openalex.org/W1991969013","https://openalex.org/W2003327631","https://openalex.org/W2018930571","https://openalex.org/W2025460028","https://openalex.org/W2026125283","https://openalex.org/W2030879797","https://openalex.org/W2044312186","https://openalex.org/W2045580850","https://openalex.org/W2078218819","https://openalex.org/W2084000818","https://openalex.org/W2085360399","https://openalex.org/W2106568191","https://openalex.org/W2110594353","https://openalex.org/W2111935514","https://openalex.org/W2132606418","https://openalex.org/W2134024123","https://openalex.org/W2152849188","https://openalex.org/W2173837601","https://openalex.org/W2264332843","https://openalex.org/W2314523203","https://openalex.org/W2398826216","https://openalex.org/W2523402549","https://openalex.org/W2556213489","https://openalex.org/W2558369444","https://openalex.org/W2765468026","https://openalex.org/W2774239541","https://openalex.org/W2783928473","https://openalex.org/W2792607040","https://openalex.org/W2895802227","https://openalex.org/W2897835520","https://openalex.org/W2899857132"],"related_works":["https://openalex.org/W2038216521","https://openalex.org/W2736574136","https://openalex.org/W2565286512","https://openalex.org/W3126677997","https://openalex.org/W2399955410","https://openalex.org/W3129283347","https://openalex.org/W2097377227","https://openalex.org/W2933782699","https://openalex.org/W2565238693","https://openalex.org/W1979706156"],"abstract_inverted_index":{"Speech":[0],"recognition":[1,18,192],"performance":[2],"of":[3,20,39,57,74,106,140,157,181,194],"the":[4,16,24,35,58,72,75,79,89,99,107,120,136,141,147,163,173,179,182,187,191],"machine":[5,25],"has":[6,27],"been":[7],"greatly":[8],"improved":[9],"using":[10],"artificial":[11],"intelligence.":[12],"However,":[13],"compared":[14,185],"with":[15,62],"superior":[17,76],"ability":[19],"human":[21,40,59],"auditory":[22,41,49,60],"system,":[23,42],"still":[26],"some":[28],"problems":[29],"to":[30,97,103,126,145,186],"deal":[31],"with.":[32],"Based":[33],"on":[34],"existing":[36],"physiological":[37],"principle":[38],"this":[43,69],"paper":[44],"proposes":[45],"a":[46,63,124],"novel":[47],"emergent":[48,129],"model.":[50],"This":[51,109],"model":[52,70],"simulates":[53,71],"each":[54],"key":[55],"part":[56],"pathway":[61],"deep":[64],"developmental":[65],"network":[66],"(DDN).":[67],"Furthermore,":[68],"function":[73],"colliculus":[77],"in":[78,88],"thalamus,":[80],"i.e.,":[81,135],"context":[82],"integration,":[83],"as":[84,117],"an":[85,155],"additional":[86],"layer":[87],"DDN.":[90,108],"Mel-frequency":[91],"cepstral":[92],"coefficients":[93],"(MFCC)":[94],"are":[95,143,169],"used":[96],"extract":[98],"speech":[100,165],"signal":[101],"features":[102],"be":[104],"inputs":[105],"work":[110],"is":[111],"different":[112,164],"from":[113,131],"other":[114],"previous":[115],"models":[116],"we":[118],"emphasise":[119],"mechanism":[121],"that":[122],"makes":[123],"system":[125],"develop":[127],"its":[128,132],"representations":[130],"operational":[133],"experience,":[134],"internal":[137,160],"unsupervised":[138],"neurons":[139,161],"DDN":[142],"utilised":[144],"depict":[146],"short":[148],"contexts,":[149],"and":[150,197],"competitions":[151],"among":[152],"them":[153],"afford":[154],"interpretation":[156],"how":[158],"such":[159],"denote":[162],"contexts":[166],"when":[167],"they":[168],"not":[170],"supervised":[171],"by":[172],"external":[174],"world.":[175],"Experimental":[176],"results":[177],"show":[178],"advantage":[180],"proposed":[183],"DNN":[184],"state-of-the-art":[188],"methods":[189],"for":[190],"accuracies":[193],"English":[195],"words":[196],"phrases.":[198]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}