{"id":"https://openalex.org/W2951373987","doi":"https://doi.org/10.1109/istel.2018.8661027","title":"Audio Compression Using Graph-based Transform","display_name":"Audio Compression Using Graph-based Transform","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2951373987","doi":"https://doi.org/10.1109/istel.2018.8661027","mag":"2951373987"},"language":"en","primary_location":{"id":"doi:10.1109/istel.2018.8661027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/istel.2018.8661027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th International Symposium on Telecommunications (IST)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1904.06588","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Majid Farzaneh","orcid":null},"institutions":[{"id":"https://openalex.org/I3131139297","display_name":"Iran Broadcasting University","ror":"https://ror.org/02p5wzp69","country_code":"IR","type":"education","lineage":["https://openalex.org/I3131139297"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Majid Farzaneh","raw_affiliation_strings":["Faculty of Media Technology and Engineering, Iran Broadcasting University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Media Technology and Engineering, Iran Broadcasting University, Tehran, Iran","institution_ids":["https://openalex.org/I3131139297"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rahil Mahdian Toroghi","orcid":null},"institutions":[{"id":"https://openalex.org/I3131139297","display_name":"Iran Broadcasting University","ror":"https://ror.org/02p5wzp69","country_code":"IR","type":"education","lineage":["https://openalex.org/I3131139297"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Rahil Mahdian Toroghi","raw_affiliation_strings":["Faculty of Media Technology and Engineering, Iran Broadcasting University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Media Technology and Engineering, Iran Broadcasting University, Tehran, Iran","institution_ids":["https://openalex.org/I3131139297"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mohammad Asgari","orcid":null},"institutions":[{"id":"https://openalex.org/I3131139297","display_name":"Iran Broadcasting University","ror":"https://ror.org/02p5wzp69","country_code":"IR","type":"education","lineage":["https://openalex.org/I3131139297"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Asgari","raw_affiliation_strings":["Faculty of Media Technology and Engineering, Iran Broadcasting University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Media Technology and Engineering, Iran Broadcasting University, Tehran, Iran","institution_ids":["https://openalex.org/I3131139297"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3131139297"],"apc_list":null,"apc_paid":null,"fwci":0.2127,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.59420212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"410","last_page":"415"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9973999857902527,"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":0.9973999857902527,"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":0.984000027179718,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decorrelation","display_name":"Decorrelation","score":0.8159000277519226},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.7444000244140625},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.7257999777793884},{"id":"https://openalex.org/keywords/lapped-transform","display_name":"Lapped transform","score":0.720300018787384},{"id":"https://openalex.org/keywords/modified-discrete-cosine-transform","display_name":"Modified discrete cosine transform","score":0.6761000156402588},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.42489999532699585},{"id":"https://openalex.org/keywords/s-transform","display_name":"S transform","score":0.4156999886035919},{"id":"https://openalex.org/keywords/discrete-sine-transform","display_name":"Discrete sine transform","score":0.3808000087738037},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.3707999885082245}],"concepts":[{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.8159000277519226},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.7444000244140625},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.7257999777793884},{"id":"https://openalex.org/C91458471","wikidata":"https://www.wikidata.org/wiki/Q17096468","display_name":"Lapped transform","level":5,"score":0.720300018787384},{"id":"https://openalex.org/C28726691","wikidata":"https://www.wikidata.org/wiki/Q1268231","display_name":"Modified discrete cosine transform","level":5,"score":0.6761000156402588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5041000247001648},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.42489999532699585},{"id":"https://openalex.org/C99234102","wikidata":"https://www.wikidata.org/wiki/Q7395403","display_name":"S transform","level":5,"score":0.4156999886035919},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4083000123500824},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3930000066757202},{"id":"https://openalex.org/C167058841","wikidata":"https://www.wikidata.org/wiki/Q971039","display_name":"Discrete sine transform","level":5,"score":0.3808000087738037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3799000084400177},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C153705960","wikidata":"https://www.wikidata.org/wiki/Q5163634","display_name":"Constant Q transform","level":5,"score":0.3668999969959259},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36079999804496765},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.3540000021457672},{"id":"https://openalex.org/C109308471","wikidata":"https://www.wikidata.org/wiki/Q2046647","display_name":"Karhunen\u2013Lo\u00e8ve theorem","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C98526533","wikidata":"https://www.wikidata.org/wiki/Q1691938","display_name":"Sub-band coding","level":3,"score":0.33889999985694885},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.33000001311302185},{"id":"https://openalex.org/C124828224","wikidata":"https://www.wikidata.org/wiki/Q2632668","display_name":"Macroblock","level":3,"score":0.3264999985694885},{"id":"https://openalex.org/C165443888","wikidata":"https://www.wikidata.org/wiki/Q1482183","display_name":"Transformation matrix","level":3,"score":0.30880001187324524},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.2989000082015991},{"id":"https://openalex.org/C1109138","wikidata":"https://www.wikidata.org/wiki/Q3280930","display_name":"Harmonic wavelet transform","level":5,"score":0.29789999127388},{"id":"https://openalex.org/C127220857","wikidata":"https://www.wikidata.org/wiki/Q2719318","display_name":"Audio signal processing","level":4,"score":0.2906000018119812},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2897000014781952},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.27559998631477356},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.2597000002861023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/istel.2018.8661027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/istel.2018.8661027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th International Symposium on Telecommunications (IST)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1904.06588","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.06588","pdf_url":"https://arxiv.org/pdf/1904.06588","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1904.06588","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.06588","pdf_url":"https://arxiv.org/pdf/1904.06588","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1505484906","https://openalex.org/W1660233191","https://openalex.org/W1670669358","https://openalex.org/W1779006005","https://openalex.org/W2002520467","https://openalex.org/W2010434073","https://openalex.org/W2031614119","https://openalex.org/W2067295501","https://openalex.org/W2101491865","https://openalex.org/W2138692623","https://openalex.org/W2294414102","https://openalex.org/W2593294603"],"related_works":[],"abstract_inverted_index":{"Graph-based":[0,27],"Transform":[1,28,80,84],"is":[2],"one":[3],"of":[4,53,55,88],"the":[5,16,43,56,62,69,73,89],"recent":[6],"transform":[7,75],"coding":[8],"methods":[9,76],"which":[10],"has":[11],"been":[12],"used":[13],"successfully":[14],"in":[15,86],"state-of-art":[17],"data":[18],"decorrelation":[19,87],"applications.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24,34],"propose":[25],"a":[26,36],"(GT)":[29],"for":[30,40],"audio":[31,44,90],"compression.":[32],"Hence,":[33],"introduce":[35],"proper":[37],"graph":[38,58],"structure":[39],"audio.":[41],"Then":[42],"frames":[45],"are":[46],"projected":[47],"onto":[48],"an":[49],"orthogonal":[50],"matrix":[51],"consisting":[52],"eigenvectors":[54],"introduced":[57],"matrix,":[59],"leading":[60],"to":[61],"sparse":[63],"coefficients.":[64],"The":[65],"results":[66],"show":[67],"that":[68],"proposed":[70],"method":[71],"outperforms":[72],"conventional":[74],"like":[77],"Discrete":[78],"Cosine":[79],"(DCT)":[81],"and":[82],"Walsh-Hadamard":[83],"(WHT)":[85],"signals.":[91]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-06-27T00:00:00"}
