{"id":"https://openalex.org/W1936312352","doi":"https://doi.org/10.1109/icassp.1987.1169448","title":"Speech recognition in scale space","display_name":"Speech recognition in scale space","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W1936312352","doi":"https://doi.org/10.1109/icassp.1987.1169448","mag":"1936312352"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1987.1169448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","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/A5026382065","display_name":"Richard F. Lyon","orcid":"https://orcid.org/0000-0003-2348-811X"},"institutions":[{"id":"https://openalex.org/I4210124598","display_name":"Palo Alto Institute","ror":"https://ror.org/02xf01n45","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210124598"]},{"id":"https://openalex.org/I4210090857","display_name":"Schlumberger (United States)","ror":"https://ror.org/009m79n22","country_code":"US","type":"company","lineage":["https://openalex.org/I4210090857","https://openalex.org/I4210092184"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"R. Lyon","raw_affiliation_strings":["Schlumberger Palo Alto Research, Palo Alto, CA, USA","Schulmberger Palo Alto Research, Palo Alto, CA"],"affiliations":[{"raw_affiliation_string":"Schlumberger Palo Alto Research, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210090857"]},{"raw_affiliation_string":"Schulmberger Palo Alto Research, Palo Alto, CA","institution_ids":["https://openalex.org/I4210124598"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5026382065"],"corresponding_institution_ids":["https://openalex.org/I4210090857","https://openalex.org/I4210124598"],"apc_list":null,"apc_paid":null,"fwci":0.9728,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.74583712,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"12","issue":null,"first_page":"1265","last_page":"1268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9988999962806702,"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":0.9986000061035156,"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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7849998474121094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.713617205619812},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6488156318664551},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6123447418212891},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.5497114062309265},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.49489158391952515},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.49112388491630554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.485748827457428},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47157543897628784},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4652712345123291},{"id":"https://openalex.org/keywords/scale-space","display_name":"Scale space","score":0.4418077766895294},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.43837428092956543},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.34763163328170776},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15124988555908203},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1422944962978363},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.11090907454490662},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08262771368026733}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7849998474121094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.713617205619812},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6488156318664551},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6123447418212891},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.5497114062309265},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.49489158391952515},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.49112388491630554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.485748827457428},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47157543897628784},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4652712345123291},{"id":"https://openalex.org/C99102927","wikidata":"https://www.wikidata.org/wiki/Q3058184","display_name":"Scale space","level":4,"score":0.4418077766895294},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.43837428092956543},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.34763163328170776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15124988555908203},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1422944962978363},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.11090907454490662},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08262771368026733},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.1987.1169448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.694.4288","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.694.4288","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.dicklyon.com/tech/Scans/ICASSP87_ScaleSpace-Lyon.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1480485976","https://openalex.org/W2048239603","https://openalex.org/W2130795195","https://openalex.org/W2133155955","https://openalex.org/W2148172098","https://openalex.org/W7007901192"],"related_works":["https://openalex.org/W2136652457","https://openalex.org/W2169849734","https://openalex.org/W2160171981","https://openalex.org/W2116722627","https://openalex.org/W2385954530","https://openalex.org/W1975869217","https://openalex.org/W2236912844","https://openalex.org/W2129150969","https://openalex.org/W2401728283","https://openalex.org/W2383829109"],"abstract_inverted_index":{"Scale-space":[0,92],"filtering,":[1],"proposed":[2],"by":[3],"Witkin":[4],"(ICASSP":[5],"84)":[6],"for":[7,17],"describing":[8],"natural":[9,51],"structure":[10],"in":[11,59,141],"one-dimensional":[12],"signals,":[13],"has":[14,126],"been":[15,108],"extended":[16],"application":[18],"to":[19,70,86,111,128],"segmentation":[20,153],"and":[21,78,122,158,164],"description":[22],"of":[23,26,36,38,46,50,76,90,94,102,133],"vector-valued":[24],"functions":[25],"time,":[27],"such":[28],"as":[29,140],"speech":[30],"spectrograms.":[31],"By":[32],"analyzing":[33],"the":[34,60,74,103,138,152],"rate":[35],"change":[37],"a":[39,48,99,123],"vector":[40],"trajectory":[41],"at":[42,63],"many":[43],"different":[44],"scales":[45],"time-smoothing,":[47],"tree":[49,61,154],"segments":[52,67,81],"can":[53],"be":[54],"constructed.":[55],"At":[56],"various":[57,64],"levels":[58],"(i.e.,":[62],"scales),":[65],"these":[66],"are":[68,155,166],"found":[69],"agree":[71],"well":[72],"with":[73,118,143,161],"kind":[75],"linguistically":[77],"perceptually":[79],"important":[80],"that":[82,150],"spectrogram":[83],"readers":[84],"use":[85,151],"describe":[87],"sound":[88],"patterns":[89],"speech.":[91],"segmentations":[93,117],"cochleagrams":[95],"(spectrograms":[96],"based":[97],"on":[98],"computational":[100],"model":[101],"peripheral":[104],"auditory":[105],"system)":[106],"have":[107],"experimentally":[109],"applied":[110],"word":[112,120],"recognition.":[113],"Recognition":[114],"using":[115],"fixed-scale":[116],"finite-state":[119],"models":[121],"Viterbi":[124],"search":[125],"led":[127],"speaker-independent":[129],"digit":[130],"recognition":[131,148],"accuracies":[132],"greater":[134],"than":[135],"97%,":[136],"about":[137],"same":[139],"tests":[142],"non-segmented":[144],"cochleagrams.":[145],"More":[146],"complex":[147],"algorithms":[149],"being":[156],"developed,":[157],"scale-space":[159],"experiments":[160],"connected":[162],"digits":[163],"sentences":[165],"also":[167],"underway.":[168]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
