{"id":"https://openalex.org/W4416750579","doi":"https://doi.org/10.1109/sips66314.2025.11261233","title":"Improving SSVEP BCI Spellers with Data Augmentation and Language Models","display_name":"Improving SSVEP BCI Spellers with Data Augmentation and Language Models","publication_year":2025,"publication_date":"2025-11-01","ids":{"openalex":"https://openalex.org/W4416750579","doi":"https://doi.org/10.1109/sips66314.2025.11261233"},"language":null,"primary_location":{"id":"doi:10.1109/sips66314.2025.11261233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sips66314.2025.11261233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Workshop on Signal Processing Systems (SiPS)","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/A5003446194","display_name":"Joe Zhang","orcid":"https://orcid.org/0000-0001-6040-2122"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph Zhang","raw_affiliation_strings":["Carnegie Mellon University,Biomedical Engineering,Pittsburgh,PA,USA,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Biomedical Engineering,Pittsburgh,PA,USA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101738004","display_name":"Ruiming Zhang","orcid":"https://orcid.org/0000-0002-6310-7468"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruiming Zhang","raw_affiliation_strings":["Carnegie Mellon University,Biomedical Engineering,Pittsburgh,PA,USA,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Biomedical Engineering,Pittsburgh,PA,USA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115728562","display_name":"Kipngeno Koech","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kipngeno Koech","raw_affiliation_strings":["Carnegie Mellon University,College of Engineering,Pittsburgh,PA,USA,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,College of Engineering,Pittsburgh,PA,USA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062944003","display_name":"David J. Hill","orcid":"https://orcid.org/0000-0003-4036-0839"},"institutions":[{"id":"https://openalex.org/I4210130200","display_name":"Carnegie Mellon University Africa","ror":"https://ror.org/02f33m021","country_code":"RW","type":"education","lineage":["https://openalex.org/I4210130200","https://openalex.org/I74973139"]}],"countries":["RW"],"is_corresponding":false,"raw_author_name":"David Hill","raw_affiliation_strings":["Carnegie Mellon University Africa,Robotics Institute,Kigali,BP,Rwanda,6150"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University Africa,Robotics Institute,Kigali,BP,Rwanda,6150","institution_ids":["https://openalex.org/I4210130200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115728563","display_name":"Kateryna Shapovalenko","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kateryna Shapovalenko","raw_affiliation_strings":["Carnegie Mellon University,Language Technologies Institute,Pittsburgh,PA,USA,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Language Technologies Institute,Pittsburgh,PA,USA,15213","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6126,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90745413,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9890000224113464,"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":0.9890000224113464,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.0044999998062849045,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.7771999835968018},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6047999858856201},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.5254999995231628},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5087000131607056},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.505299985408783},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.45820000767707825},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43459999561309814},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.35120001435279846},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.33489999175071716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8127999901771545},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.7771999835968018},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6047999858856201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5486999750137329},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.5254999995231628},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5087000131607056},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.505299985408783},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4627000093460083},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43459999561309814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3804999887943268},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.35120001435279846},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2791999876499176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.26980000734329224},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.2648000121116638},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2623000144958496},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sips66314.2025.11261233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sips66314.2025.11261233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Workshop on Signal Processing Systems (SiPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1995875735","https://openalex.org/W2338492816","https://openalex.org/W2345353767","https://openalex.org/W2553904372","https://openalex.org/W2559463885","https://openalex.org/W2915977493","https://openalex.org/W3037233591","https://openalex.org/W3046474724","https://openalex.org/W3198315730","https://openalex.org/W4285098698","https://openalex.org/W4293548030","https://openalex.org/W4365455526","https://openalex.org/W4368341067","https://openalex.org/W4387490442","https://openalex.org/W4391929620","https://openalex.org/W4392207948","https://openalex.org/W4395070131"],"related_works":[],"abstract_inverted_index":{"Steady-State":[0],"Visual":[1],"Evoked":[2],"Potential":[3],"(SSVEP)":[4],"spellers":[5,167],"offer":[6],"a":[7,28,61,71,108],"promising":[8],"non-invasive":[9],"Brain-Computer":[10],"Interface":[11],"(BCI)":[12],"solution":[13],"for":[14,40,146,160,172],"individuals":[15,173],"with":[16,70,114,133,174],"disabilities.":[17],"These":[18],"systems":[19],"decode":[20],"scalp-recorded":[21],"electroencephalography":[22],"(EEG)":[23],"signals":[24],"to":[25,53,74,101,119,130,168],"identify":[26],"characters":[27],"user":[29],"gazes":[30],"at,":[31],"enabling":[32],"hands-free":[33],"communication.":[34],"However,":[35],"deep":[36],"neural":[37,111],"networks":[38],"(DNNs)":[39],"SSVEP":[41,76,155],"decoding":[42],"face":[43],"critical":[44],"challenges,":[45],"including":[46],"high":[47],"EEG":[48],"variability":[49],"and":[50,97,164],"poor":[51],"generalization":[52],"unseen":[54,141],"subjects.":[55],"In":[56],"this":[57],"work,":[58],"we":[59,86,106],"introduce":[60],"novel":[62],"hybrid":[63,135],"framework":[64],"that":[65],"integrates":[66],"domain-specific":[67],"data":[68],"augmentation":[69,89],"language":[72],"model":[73,103,136],"enhance":[75],"speller":[77],"performance.":[78],"Leveraging":[79],"the":[80,134,152,158],"Benchmark":[81],"dataset":[82],"from":[83],"Tsinghua":[84],"University,":[85],"systematically":[87],"evaluate":[88],"techniques":[90],"such":[91],"as":[92],"frequency":[93],"masking,":[94,96],"time":[95],"noise":[98],"injection,":[99],"aiming":[100],"improve":[102,169],"robustness.":[104],"Additionally,":[105],"integrate":[107],"character-based":[109],"recurrent":[110],"network":[112],"(CharRNN)":[113],"EEGNet,":[115],"incorporating":[116],"linguistic":[117],"priors":[118],"refine":[120],"character":[121],"predictions.":[122],"Our":[123],"results":[124],"show":[125],"accuracy":[126],"gains":[127],"of":[128,154],"up":[129],"$2.9":[131],"\\%$,":[132],"significantly":[137],"improving":[138],"performance":[139],"on":[140],"subjects,":[142],"demonstrating":[143],"its":[144],"potential":[145],"real-world":[147],"applications.":[148],"This":[149],"study":[150],"advances":[151],"state":[153],"decoding,":[156],"paving":[157],"way":[159],"more":[161],"robust,":[162],"generalizable,":[163],"high-performance":[165],"BCI":[166],"communication":[170],"accessibility":[171],"severe":[175],"motor":[176],"impairments.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-28T00:00:00"}
