{"id":"https://openalex.org/W2938799435","doi":"https://doi.org/10.1109/icassp.2019.8683060","title":"Stochastic Markov Recurrent Neural Network for Source Separation","display_name":"Stochastic Markov Recurrent Neural Network for Source Separation","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2938799435","doi":"https://doi.org/10.1109/icassp.2019.8683060","mag":"2938799435"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8683060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5061908942","display_name":"Jen\u2010Tzung Chien","orcid":"https://orcid.org/0000-0003-3466-8941"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jen-Tzung Chien","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032182651","display_name":"Che-Yu Kuo","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Che-Yu Kuo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8072","last_page":"8076"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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":1.0,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.998199999332428,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7225102186203003},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.6203424334526062},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5546290278434753},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.5210120677947998},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.5169610381126404},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5071239471435547},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.48895537853240967},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.48608115315437317},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4822691082954407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4444008767604828},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42904597520828247},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3832857608795166},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3314563035964966},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26457059383392334},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.167422354221344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7225102186203003},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.6203424334526062},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5546290278434753},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5210120677947998},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.5169610381126404},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5071239471435547},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.48895537853240967},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.48608115315437317},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4822691082954407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4444008767604828},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42904597520828247},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3832857608795166},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3314563035964966},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26457059383392334},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.167422354221344},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8683060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8683060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W76597279","https://openalex.org/W592244745","https://openalex.org/W1591801644","https://openalex.org/W1884859883","https://openalex.org/W1959608418","https://openalex.org/W2032345535","https://openalex.org/W2102423079","https://openalex.org/W2106219595","https://openalex.org/W2149757909","https://openalex.org/W2167555312","https://openalex.org/W2183821610","https://openalex.org/W2212703438","https://openalex.org/W2242047860","https://openalex.org/W2396566817","https://openalex.org/W2404724332","https://openalex.org/W2405331948","https://openalex.org/W2547875792","https://openalex.org/W2548228487","https://openalex.org/W2734774145","https://openalex.org/W2749679082","https://openalex.org/W2771697229","https://openalex.org/W2889008527","https://openalex.org/W2898944992","https://openalex.org/W2962824919","https://openalex.org/W2962904371","https://openalex.org/W2963266340","https://openalex.org/W2963279312","https://openalex.org/W2963524109","https://openalex.org/W2964076986","https://openalex.org/W3033736971","https://openalex.org/W4300802867","https://openalex.org/W6603233860","https://openalex.org/W6617744952","https://openalex.org/W6635446068","https://openalex.org/W6639735774","https://openalex.org/W6640963894","https://openalex.org/W6675835146","https://openalex.org/W6688167117","https://openalex.org/W6712395597","https://openalex.org/W6729448088","https://openalex.org/W6730091202","https://openalex.org/W6738539399","https://openalex.org/W6743300111","https://openalex.org/W6754395538"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3022820045","https://openalex.org/W2801655600","https://openalex.org/W3005627584","https://openalex.org/W4303493643"],"abstract_inverted_index":{"Monaural":[0],"source":[1,16,72,89,156],"separation":[2,107],"based":[3,18],"on":[4,19,172],"recurrent":[5],"neural":[6],"network":[7],"is":[8,46,91,115,139,161],"learned":[9,92],"to":[10,32,87,117,141],"characterize":[11],"the":[12,54,57,67,81,84,102,119,126,143,164,176,179,192],"sequential":[13,133],"patterns":[14],"in":[15,62,71,147,163,184],"signals":[17,90,124,154],"dynamic":[20],"states":[21,29],"which":[22,100],"are":[23,30],"propagated":[24],"through":[25],"time.":[26,110],"The":[27,158],"hidden":[28],"assumed":[31],"be":[33],"deterministic":[34],"along":[35],"a":[36,40,76,94],"single":[37],"path":[38],"where":[39,80],"shared":[41],"long":[42],"short-term":[43,187],"memory":[44],"(LSTM)":[45],"used.":[47],"Such":[48],"assumptions":[49],"may":[50],"not":[51],"faithfully":[52],"reflect":[53],"randomness":[55],"and":[56,149,155],"variety":[58],"of":[59,69,97,113,122,129,178,186,191],"temporal":[60,123],"features":[61],"mixed":[63,85,153],"signals.":[64,157],"To":[65],"strengthen":[66],"capability":[68],"LSTM":[70,79,104,183],"separation,":[73],"we":[74],"propose":[75],"stochastic":[77,95,127,181],"Markov":[78,98,169,182],"regression":[82],"from":[83],"signal":[86,106],"its":[88],"with":[93,167],"indicator":[96],"state":[99,130,137],"selects":[101],"state-dependent":[103],"for":[105,132],"at":[108],"each":[109],"A":[111,135],"set":[112],"LSTMs":[114],"discovered":[116],"capture":[118],"structural":[120,150],"diversity":[121],"or":[125],"trajectory":[128],"transitions":[131],"prediction.":[134],"new":[136],"machine":[138],"constructed":[140],"learn":[142],"complicated":[144],"latent":[145],"semantics":[146],"heterogeneous":[148],"mappings":[151],"between":[152],"Gumbel-softmax":[159],"sampling":[160],"implemented":[162],"backpropagation":[165],"algorithm":[166],"discrete":[168],"states.":[170],"Experiments":[171],"speech":[173],"enhancement":[174],"illustrate":[175],"merit":[177],"proposed":[180],"terms":[185],"objective":[188],"intelligibility":[189],"measure":[190],"separated":[193],"speech.":[194]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}