{"id":"https://openalex.org/W4404037588","doi":"https://doi.org/10.1109/mlsp58920.2024.10734824","title":"Ultra-Low Memory Speech Denoising using Quantization-Aware Neural Architecture Search","display_name":"Ultra-Low Memory Speech Denoising using Quantization-Aware Neural Architecture Search","publication_year":2024,"publication_date":"2024-09-22","ids":{"openalex":"https://openalex.org/W4404037588","doi":"https://doi.org/10.1109/mlsp58920.2024.10734824"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp58920.2024.10734824","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp58920.2024.10734824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-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/A5007136125","display_name":"Anastasios Vafeiadis","orcid":"https://orcid.org/0000-0003-1102-5708"},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Anastasios Vafeiadis","raw_affiliation_strings":["NXP Semiconductors"],"affiliations":[{"raw_affiliation_string":"NXP Semiconductors","institution_ids":["https://openalex.org/I4210123704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043133033","display_name":"Nick van de Waterlaat","orcid":"https://orcid.org/0000-0002-4577-6481"},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nick van de Waterlaat","raw_affiliation_strings":["NXP Semiconductors"],"affiliations":[{"raw_affiliation_string":"NXP Semiconductors","institution_ids":["https://openalex.org/I4210123704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086941152","display_name":"Clement Castel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Clement Castel","raw_affiliation_strings":["NXP Semiconductors"],"affiliations":[{"raw_affiliation_string":"NXP Semiconductors","institution_ids":["https://openalex.org/I4210123704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034770088","display_name":"Bruno Defraene","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bruno Defraene","raw_affiliation_strings":["NXP Semiconductors"],"affiliations":[{"raw_affiliation_string":"NXP Semiconductors","institution_ids":["https://openalex.org/I4210123704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035751175","display_name":"G. H. O. Daalderop","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gerardo Daalderop","raw_affiliation_strings":["NXP Semiconductors"],"affiliations":[{"raw_affiliation_string":"NXP Semiconductors","institution_ids":["https://openalex.org/I4210123704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068281413","display_name":"S. Vogel","orcid":"https://orcid.org/0000-0001-9665-6562"},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Vogel","raw_affiliation_strings":["NXP Semiconductors"],"affiliations":[{"raw_affiliation_string":"NXP Semiconductors","institution_ids":["https://openalex.org/I4210123704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114513571","display_name":"Christophe Macours","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christophe Macours","raw_affiliation_strings":["NXP Semiconductors"],"affiliations":[{"raw_affiliation_string":"NXP Semiconductors","institution_ids":["https://openalex.org/I4210123704"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5007136125"],"corresponding_institution_ids":["https://openalex.org/I4210123704"],"apc_list":null,"apc_paid":null,"fwci":0.3626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68457581,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9894999861717224,"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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9894999861717224,"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/T10860","display_name":"Speech and Audio Processing","score":0.9789000153541565,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9693999886512756,"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/computer-science","display_name":"Computer science","score":0.6984704732894897},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6308959126472473},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.581730842590332},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5233763456344604},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5037078261375427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40850189328193665},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3792192041873932},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20646607875823975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984704732894897},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6308959126472473},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.581730842590332},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5233763456344604},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5037078261375427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40850189328193665},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3792192041873932},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20646607875823975},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp58920.2024.10734824","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mlsp58920.2024.10734824","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6891322245","display_name":null,"funder_award_id":"101097300","funder_id":"https://openalex.org/F4320319005","funder_display_name":"Key Digital Technologies Joint Undertaking"}],"funders":[{"id":"https://openalex.org/F4320319005","display_name":"Key Digital Technologies Joint Undertaking","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1552314771","https://openalex.org/W2492794003","https://openalex.org/W2946547492","https://openalex.org/W2962843322","https://openalex.org/W2964515685","https://openalex.org/W2981406437","https://openalex.org/W3096408984","https://openalex.org/W3160085755","https://openalex.org/W3160129476","https://openalex.org/W3192682950","https://openalex.org/W4221162870","https://openalex.org/W4226389608","https://openalex.org/W4312570973","https://openalex.org/W4379116015","https://openalex.org/W4380434618","https://openalex.org/W4395447416","https://openalex.org/W4399497076","https://openalex.org/W6680017764","https://openalex.org/W6759828284"],"related_works":["https://openalex.org/W2588198209","https://openalex.org/W1909006023","https://openalex.org/W4205824991","https://openalex.org/W3200723557","https://openalex.org/W2979160909","https://openalex.org/W2114837856","https://openalex.org/W4312713546","https://openalex.org/W2362195430","https://openalex.org/W2347494122","https://openalex.org/W2567983276"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2,119],"a":[3,29,48,57,109,120],"novel":[4],"neural":[5,25,157],"network-based":[6,158],"speech":[7,41,79,141,159],"denoising":[8,42,80,142],"approach":[9,53],"designed":[10],"for":[11,154],"operation":[12],"on":[13,164],"ultra-low":[14],"memory":[15,30,83,100],"devices":[16],"such":[17],"as,":[18],"e.g.,":[19],"gaming":[20,132],"headsets.":[21],"We":[22,145],"show":[23],"that":[24,87],"network":[26],"models":[27],"with":[28],"footprint":[31],"in":[32,56,98,113],"the":[33,76,126,130,140],"range":[34],"of":[35,129],"15\u201330":[36],"kB":[37],"can":[38,149],"achieve":[39],"effective":[40],"performance.":[43],"First,":[44],"to":[45,74,95,103,124,138],"this":[46,117],"end,":[47],"Neural":[49,62,67],"Architecture":[50],"Search":[51],"(NAS)":[52],"is":[54,73],"proposed":[55],"search":[58],"space":[59],"encompassing":[60],"Convolutional":[61],"Networks":[63,68],"(CNNs)":[64],"and":[65,82,160],"Recurrent":[66,89],"(RNN":[69],"s).":[70],"The":[71],"goal":[72],"optimize":[75,139],"trade-off":[77],"between":[78],"performance":[81,143],"usage.":[84],"Experiments":[85],"indicate":[86],"Gated":[88],"Units":[90],"(GRUs)":[91],"are":[92],"particularly":[93],"prone":[94],"quantization":[96],"issues":[97],"tight":[99],"conditions":[101],"compared":[102],"Long":[104],"Short-Term":[105],"Memory":[106],"(LSTM)":[107],"RNNs,":[108],"phenomenon":[110],"not":[111],"explored":[112],"prior":[114],"research.":[115],"Secondly,":[116],"work":[118],"data":[121],"preprocessing":[122],"technique":[123],"model":[125],"microphone":[127],"characteristics":[128],"target":[131],"headset":[133],"device,":[134],"which":[135],"further":[136],"helps":[137],"on-device.":[144],"believe":[146],"these":[147],"findings":[148],"serve":[150],"as":[151],"future":[152],"guidance":[153],"deploying":[155],"sophisticated":[156],"audio":[161],"processing":[162],"algorithms":[163],"resource-constrained":[165],"edge":[166],"devices.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}