{"id":"https://openalex.org/W7167573567","doi":"https://doi.org/10.48550/arxiv.2607.03844","title":"EEG-Based Imagined Speech Decoding Using a Hybrid CNN-SNN Architecture","display_name":"EEG-Based Imagined Speech Decoding Using a Hybrid CNN-SNN Architecture","publication_year":2026,"publication_date":"2026-07-04","ids":{"openalex":"https://openalex.org/W7167573567","doi":"https://doi.org/10.48550/arxiv.2607.03844"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.03844","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.03844","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.03844","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140156067","display_name":"Fatima Shalhoub","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shalhoub, Fatima","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140156335","display_name":"Mariam Al Mawla","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mawla, Mariam Al","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031346919","display_name":"Kabalan Chaccour","orcid":"https://orcid.org/0000-0002-3731-7787"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaccour, Kabalan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134148632","display_name":"Iv\u00e1n L\u00f3pez-Espejo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"L\u00f3pez-Espejo, Iv\u00e1n","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5078058077","display_name":"Hoda Fares","orcid":"https://orcid.org/0000-0003-0460-7611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fares, Hoda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.002300000051036477,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.0017999999690800905,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7513999938964844},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6435999870300293},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5403000116348267},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43220001459121704},{"id":"https://openalex.org/keywords/neural-decoding","display_name":"Neural decoding","score":0.4239000082015991},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.3783999979496002},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.3377000093460083},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.32499998807907104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7684000134468079},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7513999938964844},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6435999870300293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443000197410583},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5403000116348267},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5339999794960022},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43220001459121704},{"id":"https://openalex.org/C40743351","wikidata":"https://www.wikidata.org/wiki/Q7002049","display_name":"Neural decoding","level":3,"score":0.4239000082015991},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.3783999979496002},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3181000053882599},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31119999289512634},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.2953000068664551},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.28119999170303345},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25769999623298645}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.03844","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.03844","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.03844","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.03844","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.44977492094039917,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Imagined":[0],"speech":[1,25,30,122],"decoding":[2,28,89,166],"using":[3,95],"EEG":[4,45],"signals":[5],"has":[6],"emerged":[7],"as":[8],"a":[9,32,87],"promising":[10],"frontier":[11],"in":[12,148],"brain-computer":[13],"interface":[14],"(BCI)":[15],"research,":[16],"particularly":[17],"to":[18,36,61,116,152],"restore":[19],"communication":[20],"for":[21,167,177],"individuals":[22],"with":[23],"severe":[24],"impairments.":[26],"However,":[27],"imagined":[29,121,168],"remains":[31],"complex":[33],"task":[34],"due":[35],"the":[37,113,128,138,149,161,171],"non-stationary,":[38],"low-amplitude,":[39],"and":[40],"highly":[41],"variable":[42],"nature":[43],"of":[44,70,135,163,173],"signals.":[46],"Existing":[47],"methods":[48,146],"often":[49],"rely":[50],"on":[51,137],"classical":[52],"machine":[53],"learning":[54,57],"or":[55,66],"deep":[56],"models":[58],"that":[59,91,127],"fail":[60],"exploit":[62],"spike-based":[63,164],"temporal":[64,93,104,165],"dynamics":[65],"event-driven":[67],"firing":[68],"mechanisms":[69],"biological":[71],"neurons,":[72],"which":[73],"are":[74],"naturally":[75],"modeled":[76],"by":[77,101],"spiking":[78],"neural":[79,97],"networks":[80,98],"(SNNs).":[81],"In":[82],"this":[83,111],"study,":[84],"we":[85],"propose":[86],"hybrid":[88],"pipeline":[90],"extracts":[92],"representations":[94],"convolutional":[96],"(CNNs)":[99],"followed":[100],"biologically":[102,174],"inspired":[103],"classification":[105],"via":[106],"SNNs.":[107],"To":[108],"our":[109],"knowledge,":[110],"is":[112],"first":[114],"study":[115],"integrate":[117],"SNNs":[118],"into":[119],"EEG-based":[120],"decoding.":[123],"Experimental":[124],"results":[125],"show":[126],"proposed":[129],"CNN-SNN":[130],"architecture":[131],"achieves":[132],"an":[133],"accuracy":[134],"80.13%":[136],"2020":[139],"BCI":[140,181],"Competition":[141],"III":[142],"benchmark,":[143],"surpassing":[144],"existing":[145],"reported":[147],"literature":[150],"(up":[151],"70.19%)":[153],"under":[154],"comparable":[155],"evaluation":[156],"settings.":[157],"These":[158],"findings":[159],"demonstrate":[160],"effectiveness":[162],"speech,":[169],"highlighting":[170],"promise":[172],"grounded":[175],"pipelines":[176],"next":[178],"generation":[179],"neuromorphic":[180],"applications.":[182]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-08T00:00:00"}
