{"id":"https://openalex.org/W1485837325","doi":"https://doi.org/10.1109/icassp.1986.1168591","title":"A novel approach to estimating excitation code in code-excited linear prediction coding","display_name":"A novel approach to estimating excitation code in code-excited linear prediction coding","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W1485837325","doi":"https://doi.org/10.1109/icassp.1986.1168591","mag":"1485837325"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1986.1168591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1986.1168591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '86. 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/A5005895221","display_name":"Ghen Ohyama","orcid":null},"institutions":[{"id":"https://openalex.org/I1285200648","display_name":"Ministry of Internal Affairs and Communications","ror":"https://ror.org/00vs1pz50","country_code":"JP","type":"government","lineage":["https://openalex.org/I1285200648","https://openalex.org/I2802531770"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"G. Ohyama","raw_affiliation_strings":["Radio Research Laboratory, Ministry of Posts and Telecommunications, Koganei, Tokyo, Japan","Ministry of Posts and Telecommunications, Tokyo, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Radio Research Laboratory, Ministry of Posts and Telecommunications, Koganei, Tokyo, Japan","institution_ids":[]},{"raw_affiliation_string":"Ministry of Posts and Telecommunications, Tokyo, Japan#TAB#","institution_ids":["https://openalex.org/I1285200648"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5005895221"],"corresponding_institution_ids":["https://openalex.org/I1285200648"],"apc_list":null,"apc_paid":null,"fwci":0.2937,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55938686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"3067","last_page":"3070"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9944999814033508,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9944999814033508,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9700000286102295,"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/linear-prediction","display_name":"Linear prediction","score":0.7949107885360718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7136610150337219},{"id":"https://openalex.org/keywords/vector-sum-excited-linear-prediction","display_name":"Vector sum excited linear prediction","score":0.6933194398880005},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6367202401161194},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.5437972545623779},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5395902395248413},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.5228871703147888},{"id":"https://openalex.org/keywords/code-excited-linear-prediction","display_name":"Code-excited linear prediction","score":0.49811506271362305},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4799397587776184},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.46667778491973877},{"id":"https://openalex.org/keywords/coding-gain","display_name":"Coding gain","score":0.4514075219631195},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.44789135456085205},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.4341456890106201},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3321261405944824},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.190277099609375},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14339467883110046}],"concepts":[{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.7949107885360718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7136610150337219},{"id":"https://openalex.org/C138807605","wikidata":"https://www.wikidata.org/wiki/Q7917845","display_name":"Vector sum excited linear prediction","level":5,"score":0.6933194398880005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6367202401161194},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.5437972545623779},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5395902395248413},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.5228871703147888},{"id":"https://openalex.org/C105964291","wikidata":"https://www.wikidata.org/wiki/Q856184","display_name":"Code-excited linear prediction","level":4,"score":0.49811506271362305},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4799397587776184},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.46667778491973877},{"id":"https://openalex.org/C76862118","wikidata":"https://www.wikidata.org/wiki/Q1105671","display_name":"Coding gain","level":3,"score":0.4514075219631195},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.44789135456085205},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.4341456890106201},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3321261405944824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.190277099609375},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14339467883110046},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1986.1168591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1986.1168591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1982751076","https://openalex.org/W2051489660","https://openalex.org/W1629698752","https://openalex.org/W1570840316","https://openalex.org/W2119342582","https://openalex.org/W2148904379","https://openalex.org/W2350749055","https://openalex.org/W4301029372","https://openalex.org/W2114934544","https://openalex.org/W2111369522"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,19,27],"new":[4],"method":[5,104],"for":[6,26],"selecting":[7],"the":[8,13,33,36,40,43,48,59,68,73,77,80,91,109],"excitation":[9],"codes":[10],"and":[11,39,79],"estimating":[12],"long-term":[14,37],"prediction":[15,23,34,44,60,78],"coefficients":[16,38],"simultaneously":[17],"in":[18,55],"simplified":[20],"code-excited":[21],"linear":[22],"coding":[24],"suitable":[25],"low":[28],"bit":[29],"rate":[30],"transmission.":[31],"Since":[32],"of":[35,42,93,99],"replacement":[41,81],"error":[45,61],"signal":[46,62],"with":[47,67],"noise":[49,69],"sequence":[50,70],"are":[51,82],"carried":[52,83],"out":[53,84],"sequentially":[54],"our":[56],"previous":[57],"system,":[58],"does":[63],"not":[64],"always":[65],"match":[66],"well.":[71],"In":[72],"system":[74],"proposed":[75,103],"here,":[76],"simultaneously.":[85],"The":[86],"experimental":[87],"results":[88],"show":[89],"that":[90],"quality":[92],"synthesized":[94],"speech":[95,101],"is":[96],"good.":[97],"Examples":[98],"processed":[100],"by":[102],"will":[105],"be":[106],"demonstrated":[107],"at":[108],"conference.":[110]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}