{"id":"https://openalex.org/W2052108067","doi":"https://doi.org/10.4304/jsw.5.7.705-712","title":"Feature Extraction in Speechreading","display_name":"Feature Extraction in Speechreading","publication_year":2010,"publication_date":"2010-06-16","ids":{"openalex":"https://openalex.org/W2052108067","doi":"https://doi.org/10.4304/jsw.5.7.705-712","mag":"2052108067"},"language":"en","primary_location":{"id":"doi:10.4304/jsw.5.7.705-712","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jsw.5.7.705-712","pdf_url":null,"source":{"id":"https://openalex.org/S114141714","display_name":"Journal of Software","issn_l":"1796-217X","issn":["1796-217X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Software","raw_type":"journal-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/A5017118967","display_name":"Jun He","orcid":"https://orcid.org/0000-0002-3781-9234"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jun He","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100408716","display_name":"Hua Zhang","orcid":"https://orcid.org/0000-0002-7627-4142"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hua Zhang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017118967"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13267157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"7","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9919000267982483,"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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9919000267982483,"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/T10860","display_name":"Speech and Audio Processing","score":0.9810000061988831,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9775000214576721,"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":0.9134485721588135},{"id":"https://openalex.org/keywords/speechreading","display_name":"Speechreading","score":0.8271384239196777},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5863581895828247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4900442361831665},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44810643792152405},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.42232269048690796},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3679324984550476},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.20067530870437622},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.034574419260025024}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9134485721588135},{"id":"https://openalex.org/C2910309083","wikidata":"https://www.wikidata.org/wiki/Q1069953","display_name":"Speechreading","level":2,"score":0.8271384239196777},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5863581895828247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4900442361831665},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44810643792152405},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.42232269048690796},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3679324984550476},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.20067530870437622},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.034574419260025024},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4304/jsw.5.7.705-712","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jsw.5.7.705-712","pdf_url":null,"source":{"id":"https://openalex.org/S114141714","display_name":"Journal of Software","issn_l":"1796-217X","issn":["1796-217X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Software","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1527102103","https://openalex.org/W1529401398","https://openalex.org/W1549965231","https://openalex.org/W1554901277","https://openalex.org/W1919971835","https://openalex.org/W1978380426","https://openalex.org/W2031693516","https://openalex.org/W2096391593","https://openalex.org/W2104095591","https://openalex.org/W2111229122","https://openalex.org/W2113814270","https://openalex.org/W2121015323","https://openalex.org/W2121430128","https://openalex.org/W2121486117","https://openalex.org/W2151043030","https://openalex.org/W2152051032","https://openalex.org/W2153511051","https://openalex.org/W2157190406","https://openalex.org/W2166846876","https://openalex.org/W2172803778","https://openalex.org/W3099202502"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2056912418","https://openalex.org/W2112208972","https://openalex.org/W2123759770","https://openalex.org/W2033213769","https://openalex.org/W2811390910","https://openalex.org/W4312376745","https://openalex.org/W2768048376","https://openalex.org/W2082269393"],"abstract_inverted_index":{"To":[0],"solve":[1],"the":[2,69,122,143],"problem":[3],"of":[4],"feature":[7,13,70,138,194],"extraction":[8,14,139,195],"in":[9,26,116,149,199],"speechreading,":[10],"several":[11],"appearance-based":[12,193],"method":[15,155],"are":[16],"compared":[17],"and":[18,153],"a":[19],"new":[20],"improved":[21],"LDA":[22,80,93],"algorithm":[23,94,187,196],"is":[24,104,118,188,205],"proposed":[25],"this":[27,78,88,186],"paper.":[28],"I":[29],"n":[31],"speech":[32],"or":[33,62],"speechreading":[34,117],"recognition":[35,86,115],"application,":[36],"Linear":[41,131],"Discriminant":[42,132],"Analysis":[43],"(LDA)":[45],"usually":[50],"choose":[51,121],"syllable":[54],"\u3001":[57],"HMM":[60],"state":[61],"other":[63,192],"units":[64],"as":[65,127],"class":[66,128],"unit.":[67],"but":[68],"dimensionality":[71],"reduction":[72],"direction":[75],"based":[76,95],"on":[77,96,173],"traditional":[79],"have":[81],"no":[82],"direct":[83],"relations":[84],"with":[85],"accuracy,To":[87],"problem,":[89],"A":[92],"Object":[97],"(LDAO)":[102],"which":[103,134],"fit":[107],"for":[110,156],"isolated":[113],"words":[114],"proposed,":[119],"LDAO":[120,157,202],"objects":[123,148],"to":[124,130,190],"be":[125],"recognized":[126],"unit":[129],"Analysis,":[133],"guarantees":[135],"follow":[142],"most":[144],"discriminant":[145],"directions":[146],"among":[147],"theory.":[150],"Subsequently,":[151],"training":[152],"recognizing":[154],"was":[160],"also":[163],"given.":[164],"All":[167],"experiments":[170],"were":[171],"performed":[172],"bimodal":[174],"database":[175],",":[177],"Experimental":[180],"results":[181],"showed":[182],"that":[185],"superior":[189],"any":[191],"speechreading.":[200],"Specifically,":[201],"better":[206],"than":[207],"DCT+LDA":[208],"about":[209],"3%":[210],".":[212]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
