{"id":"https://openalex.org/W7163170516","doi":"https://doi.org/10.48550/arxiv.2606.01135","title":"Spiking and Event-driven Neuromorphic Mamba Models for Efficient Speech Recognition","display_name":"Spiking and Event-driven Neuromorphic Mamba Models for Efficient Speech Recognition","publication_year":2026,"publication_date":"2026-05-31","ids":{"openalex":"https://openalex.org/W7163170516","doi":"https://doi.org/10.48550/arxiv.2606.01135"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.01135","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01135","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2606.01135","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137699938","display_name":"Tauseef Ahmed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmed, Tauseef","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137638263","display_name":"Tao Sun","orcid":"https://orcid.org/0000-0002-7575-3483"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137637061","display_name":"Jeronimo Castrillon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Castrillon, Jeronimo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069508579","display_name":"Kanishkan Vadivel","orcid":"https://orcid.org/0000-0003-4186-9530"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vadivel, Kanishkan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5037310533","display_name":"Guangzhi Tang","orcid":"https://orcid.org/0000-0002-0204-9225"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Guangzhi","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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.6327000260353088,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.6327000260353088,"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"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.27300000190734863,"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"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.031599998474121094,"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/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.9695000052452087},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.7955999970436096},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5759999752044678},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5701000094413757},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5013999938964844},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4984999895095825},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.44780001044273376},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.37630000710487366}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.9695000052452087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7971000075340271},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.7955999970436096},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5759999752044678},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5701000094413757},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.520799994468689},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5013999938964844},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4984999895095825},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.44780001044273376},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3926999866962433},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.37630000710487366},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32420000433921814},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3215999901294708},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.29910001158714294},{"id":"https://openalex.org/C33010914","wikidata":"https://www.wikidata.org/wiki/Q7291980","display_name":"Random neural network","level":4,"score":0.2736000120639801},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.2662999927997589},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.01135","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01135","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.01135","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01135","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2],"greatly":[3],"advanced":[4],"automatic":[5],"speech":[6],"recognition":[7],"(ASR),":[8],"enabling":[9,153],"widespread":[10],"deployment":[11],"on":[12,125],"edge":[13],"devices":[14],"such":[15,36],"as":[16],"smartphones":[17],"and":[18,25,41,60,90,163],"smart":[19],"home":[20],"systems.":[21],"However,":[22,70],"the":[23,75,100],"computational":[24,161],"energy":[26],"demands":[27],"of":[28,78],"deep":[29],"neural":[30,57,62,93],"networks":[31,58,94],"pose":[32],"significant":[33],"challenges":[34],"for":[35,84,104],"resource-constrained":[37],"deployments,":[38],"introducing":[39,52],"latency":[40],"limiting":[42],"real-time":[43],"interaction.":[44],"Neuromorphic":[45],"computing":[46],"offers":[47],"a":[48,71,130,149],"promising":[49],"solution":[50],"by":[51],"activation":[53,97,117],"sparsity":[54,98,118,137],"through":[55],"spiking":[56,89,131],"(SNNs)":[59],"event-driven":[61,91,109,151],"networks,":[63],"converting":[64],"dense":[65],"operations":[66],"into":[67],"sparse":[68],"computations.":[69],"study":[72],"that":[73,133],"evaluates":[74],"hardware":[76],"benefits":[77],"different":[79],"neuromorphic":[80,92],"strategies":[81],"remains":[82],"lacking":[83],"ASR.":[85,105],"This":[86],"paper":[87],"explores":[88],"to":[95],"improve":[96],"in":[99],"state-of-the-art":[101],"SpeechMamba":[102,110,132],"model":[103],"We":[106,127],"introduce":[107],"an":[108],"with":[111,119],"FATReLU":[112],"activation,":[113],"achieving":[114],"over":[115,135,165],"60%":[116],"less":[120],"than":[121,143],"1%":[122],"accuracy":[123],"degradation":[124],"LibriSpeech.":[126],"also":[128],"propose":[129],"attains":[134],"70%":[136],"while":[138],"using":[139],"30%":[140],"fewer":[141],"parameters":[142],"comparable":[144],"SNNs.":[145],"Finally,":[146],"we":[147],"develop":[148],"cycle-accurate":[150],"simulator":[152],"flexible":[154],"algorithm-hardware":[155],"co-exploration,":[156],"which":[157],"helps":[158],"us":[159],"identify":[160],"bottlenecks":[162],"yields":[164],"10%":[166],"additional":[167],"efficiency":[168],"improvements.":[169]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-03T00:00:00"}