{"id":"https://openalex.org/W2097924706","doi":"https://doi.org/10.1109/tcom.1987.1096884","title":"Gain-Adaptive Vector Quantization with Application to Speech Coding","display_name":"Gain-Adaptive Vector Quantization with Application to Speech Coding","publication_year":1987,"publication_date":"1987-09-01","ids":{"openalex":"https://openalex.org/W2097924706","doi":"https://doi.org/10.1109/tcom.1987.1096884","mag":"2097924706"},"language":"en","primary_location":{"id":"doi:10.1109/tcom.1987.1096884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcom.1987.1096884","pdf_url":null,"source":{"id":"https://openalex.org/S4210170832","display_name":"IRE Transactions on Communications Systems","issn_l":"0096-2244","issn":["0096-2244","2162-2132"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Communications","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/A5065966638","display_name":"Juin-Hwey Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I131579929","display_name":"Mansfield University","ror":"https://ror.org/01emtgd92","country_code":"US","type":"education","lineage":["https://openalex.org/I131579929"]},{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juin-Hwey Chen","raw_affiliation_strings":["Codex Corporation, Mansfield, MA, USA","Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Codex Corporation, Mansfield, MA, USA","institution_ids":["https://openalex.org/I131579929"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016272725","display_name":"A. Gersho","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Gersho","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8692,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.93395749,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"35","issue":"9","first_page":"918","last_page":"930"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":1.0,"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":1.0,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.994700014591217,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.8134328126907349},{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.7572083473205566},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.5600806474685669},{"id":"https://openalex.org/keywords/coding-gain","display_name":"Coding gain","score":0.550613522529602},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.47939467430114746},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47885844111442566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46786263585090637},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4557208716869354},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.43092644214630127},{"id":"https://openalex.org/keywords/code-excited-linear-prediction","display_name":"Code-excited linear prediction","score":0.42103472352027893},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37369972467422485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2666628360748291},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.25435343384742737},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.2310270071029663},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07796496152877808}],"concepts":[{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.8134328126907349},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.7572083473205566},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.5600806474685669},{"id":"https://openalex.org/C76862118","wikidata":"https://www.wikidata.org/wiki/Q1105671","display_name":"Coding gain","level":3,"score":0.550613522529602},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47939467430114746},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47885844111442566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46786263585090637},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4557208716869354},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.43092644214630127},{"id":"https://openalex.org/C105964291","wikidata":"https://www.wikidata.org/wiki/Q856184","display_name":"Code-excited linear prediction","level":4,"score":0.42103472352027893},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37369972467422485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2666628360748291},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.25435343384742737},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.2310270071029663},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07796496152877808}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcom.1987.1096884","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcom.1987.1096884","pdf_url":null,"source":{"id":"https://openalex.org/S4210170832","display_name":"IRE Transactions on Communications Systems","issn_l":"0096-2244","issn":["0096-2244","2162-2132"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W99903537","https://openalex.org/W1591006912","https://openalex.org/W1606554194","https://openalex.org/W1700083040","https://openalex.org/W1823186822","https://openalex.org/W1904554885","https://openalex.org/W1983796739","https://openalex.org/W1985918015","https://openalex.org/W2002182716","https://openalex.org/W2032294274","https://openalex.org/W2037034710","https://openalex.org/W2044002522","https://openalex.org/W2048916503","https://openalex.org/W2058075673","https://openalex.org/W2065302611","https://openalex.org/W2100205678","https://openalex.org/W2103916214","https://openalex.org/W2134383396","https://openalex.org/W2135469284","https://openalex.org/W2138054245","https://openalex.org/W2186435531","https://openalex.org/W2913399920","https://openalex.org/W3044714420","https://openalex.org/W4229500460","https://openalex.org/W4244017338","https://openalex.org/W6604021822","https://openalex.org/W6635418751","https://openalex.org/W6638313880","https://openalex.org/W6675500714","https://openalex.org/W7045266920"],"related_works":["https://openalex.org/W2614570504","https://openalex.org/W4236018629","https://openalex.org/W2132539013","https://openalex.org/W3943236","https://openalex.org/W2148772884","https://openalex.org/W2017514583","https://openalex.org/W2100120615","https://openalex.org/W2014919663","https://openalex.org/W2377001183","https://openalex.org/W2534663775"],"abstract_inverted_index":{"The":[0,49,68,135],"generalization":[1],"of":[2,18,27,40,60],"gain":[3,53,105],"adaptation":[4,99],"to":[5,44,55,65,149],"vector":[6,29,63,132],"quantization":[7],"(VQ)":[8],"is":[9,21,89,145],"explored":[10],"in":[11,130,165],"this":[12],"paper":[13],"and":[14,75,97,102,109],"a":[15,25,52,57,127,162],"comprehensive":[16],"examination":[17],"alternative":[19],"techniques":[20],"presented.":[22],"We":[23],"introduce":[24],"class":[26],"adaptive":[28],"quantizers":[30],"that":[31],"can":[32,76,113],"dynamically":[33],"adjust":[34],"the":[35,45,83,85,92,140],"\"gain\"":[36],"or":[37,125],"amplitude":[38],"scale":[39],"code":[41],"vectors":[42,70],"according":[43],"input":[46,62],"signal":[47],"level.":[48],"encoder":[50],"uses":[51],"estimator":[54],"determine":[56],"suitable":[58],"normalization":[59],"each":[61],"prior":[64],"VQ":[66,86,112,143,153,160],"encoding.":[67],"normalized":[69],"have":[71],"reduced":[72],"dynamic":[73],"range":[74],"then":[77],"be":[78,114],"more":[79],"efficiently":[80],"coded.":[81],"At":[82],"receiver,":[84],"decoder":[87],"output":[88],"multiplied":[90],"by":[91],"estimated":[93],"gain.":[94],"Both":[95],"forward":[96],"backward":[98],"are":[100,107],"considered":[101],"several":[103],"different":[104],"estimators":[106],"compared":[108],"evaluated.":[110],"Gain-adaptive":[111],"used":[115],"alone":[116],"for":[117,138],"\"vector":[118],"PCM\"":[119],"coding":[120,133],"(i.e.,":[121],"direct":[122],"waveform":[123],"VQ)":[124],"as":[126],"building":[128],"block":[129],"other":[131],"schemes.":[134],"design":[136],"algorithm":[137],"generating":[139],"appropriate":[141],"gain-normalized":[142],"codebook":[144],"introduced.":[146],"When":[147],"applied":[148],"speech":[150],"coding,":[151],"gain-adaptive":[152],"achieves":[154],"significant":[155],"performance":[156],"improvement":[157],"over":[158],"fixed":[159],"with":[161],"negligible":[163],"increase":[164],"complexity.":[166]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}