{"id":"https://openalex.org/W7151372057","doi":"https://doi.org/10.48550/arxiv.2604.04129","title":"Measuring Robustness of Speech Recognition from MEG Signals Under Distribution Shift","display_name":"Measuring Robustness of Speech Recognition from MEG Signals Under Distribution Shift","publication_year":2026,"publication_date":"2026-04-05","ids":{"openalex":"https://openalex.org/W7151372057","doi":"https://doi.org/10.48550/arxiv.2604.04129"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.04129","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04129","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.04129","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133128865","display_name":"Sheng-You Chien","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chien, Sheng-You","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133078200","display_name":"Bo-Yi Mao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mao, Bo-Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133081700","display_name":"Yi-Ning Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Yi-Ning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103017921","display_name":"Po\u2010Chih Kuo","orcid":"https://orcid.org/0000-0003-4020-3147"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuo, Po-Chih","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.350600004196167,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.350600004196167,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.1395999938249588,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.08299999684095383,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/normalization","display_name":"Normalization (sociology)","score":0.6675000190734863},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6031000018119812},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5945000052452087},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.569599986076355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5691999793052673},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5421000123023987},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4309000074863434}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6675000190734863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6352999806404114},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6031000018119812},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5945000052452087},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5715000033378601},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.569599986076355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5691999793052673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5465999841690063},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5421000123023987},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4309000074863434},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.04129","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04129","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.04129","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04129","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.49934402108192444,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"investigates":[2],"robust":[3],"speech-related":[4],"decoding":[5,187],"from":[6,15],"non-invasive":[7,185],"MEG":[8],"signals":[9],"using":[10],"the":[11,16,37,71,99,106,177,182,200],"LibriBrain":[12],"phoneme-classification":[13],"benchmark":[14],"2025":[17],"PNPL":[18],"competition.":[19],"We":[20],"compare":[21],"residual":[22],"convolutional":[23],"neural":[24],"networks":[25],"(CNNs),":[26],"an":[27],"STFT-based":[28],"CNN,":[29],"and":[30,48,56,92,149,151],"a":[31,83,132],"CNN--Transformer":[32],"hybrid,":[33],"while":[34,197],"also":[35,198],"examining":[36],"effects":[38],"of":[39,79,112,184,193,202],"group":[40,86],"averaging,":[41,87],"label":[42,88],"balancing,":[43,89],"repeated":[44,90],"grouping,":[45,91],"normalization":[46,68,129],"strategies,":[47],"data":[49],"augmentation.":[50],"Across":[51],"our":[52,80,113,138],"in-house":[53],"implementations,":[54],"preprocessing":[55],"data-configuration":[57],"choices":[58],"matter":[59],"more":[60,163,174],"than":[61],"additional":[62],"architectural":[63],"complexity,":[64],"among":[65],"which":[66],"instance":[67,93,116],"emerges":[69],"as":[70],"most":[72,111],"influential":[73],"modification":[74],"for":[75,105],"generalization.":[76],"The":[77],"strongest":[78],"own":[81],"models,":[82,114],"CNN":[84,108],"with":[85,103,157],"normalization,":[94,117],"achieves":[95],"60.95%":[96],"F1-macro":[97,145],"on":[98,146],"test":[100],"split,":[101],"compared":[102],"39.53%":[104],"plain":[107],"baseline.":[109],"However,":[110],"without":[115],"show":[118],"substantial":[119],"validation-to-test":[120],"degradation,":[121],"indicating":[122],"that":[123,180],"distribution":[124,195],"shift":[125,196],"induced":[126],"by":[127],"different":[128],"statistics":[130],"is":[131,154],"major":[133],"obstacle":[134],"to":[135],"generalization":[136],"in":[137],"experiments.":[139],"By":[140],"contrast,":[141],"MEGConformer":[142,172],"maintains":[143],"64.09%":[144],"both":[147],"validation":[148],"test,":[150],"saliency-map":[152],"analysis":[153],"qualitatively":[155],"consistent":[156],"this":[158],"contrast:":[159],"weaker":[160],"models":[161],"exhibit":[162],"concentrated":[164],"or":[165],"repetitive":[166],"phoneme-sensitive":[167],"patterns":[168],"across":[169],"splits,":[170],"whereas":[171],"appears":[173],"distributed.":[175],"Overall,":[176],"results":[178],"suggest":[179],"improving":[181],"reliability":[183],"phoneme":[186],"will":[188],"likely":[189],"require":[190],"better":[191],"handling":[192],"normalization-related":[194],"addressing":[199],"challenge":[201],"single-trial":[203],"decoding.":[204]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-08T00:00:00"}