{"id":"https://openalex.org/W3198011653","doi":"https://doi.org/10.21437/interspeech.2021-1984","title":"High-Fidelity and Low-Latency Universal Neural Vocoder Based on Multiband WaveRNN with Data-Driven Linear Prediction for Discrete Waveform Modeling","display_name":"High-Fidelity and Low-Latency Universal Neural Vocoder Based on Multiband WaveRNN with Data-Driven Linear Prediction for Discrete Waveform Modeling","publication_year":2021,"publication_date":"2021-08-27","ids":{"openalex":"https://openalex.org/W3198011653","doi":"https://doi.org/10.21437/interspeech.2021-1984","mag":"3198011653"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2021-1984","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2021-1984","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2021","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/A5050897938","display_name":"Patrick Lumban Tobing","orcid":"https://orcid.org/0000-0003-2792-8418"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patrick Lumban Tobing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5078330211","display_name":"Tomoki Toda","orcid":"https://orcid.org/0000-0001-8146-1279"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tomoki Toda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2217","last_page":"2221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9984999895095825,"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"}},{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9700999855995178,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/waveform","display_name":"Waveform","score":0.7571080923080444},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7472528219223022},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5655108094215393},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.5283780097961426},{"id":"https://openalex.org/keywords/linear-prediction","display_name":"Linear prediction","score":0.5106950402259827},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43936794996261597},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.43243834376335144},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37407833337783813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3604888319969177}],"concepts":[{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.7571080923080444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7472528219223022},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5655108094215393},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.5283780097961426},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.5106950402259827},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43936794996261597},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.43243834376335144},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37407833337783813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3604888319969177},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2021-1984","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2021-1984","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2021","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/W4313443006","https://openalex.org/W2945374968","https://openalex.org/W4293777179","https://openalex.org/W4385452045","https://openalex.org/W2164070813","https://openalex.org/W2135608140","https://openalex.org/W2895525995","https://openalex.org/W2332512904","https://openalex.org/W4224231624","https://openalex.org/W2319626700"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,27,43,84,88,156],"novel":[4,64,89],"high-fidelity":[5,117],"and":[6,122,134,171],"low-latency":[7,61,153],"universal":[8],"neural":[9],"vocoder":[10],"framework":[11,115],"based":[12],"on":[13,127],"multiband":[14,54],"WaveRNN":[15,30],"with":[16,42,71,101,164],"data-driven":[17,67,85],"linear":[18,68],"prediction":[19,69],"for":[20,32,66,97,120,151],"discrete":[21,72,98],"waveform":[22,35,73,99],"modeling":[23,55,74,100],"(MWDLP).":[24],"MWDLP":[25,114],"employs":[26],"coarse-fine":[28],"bit":[29],"architecture":[31],"10-bit":[33],"mu-law":[34],"modeling.":[36],"A":[37,63],"sparse":[38],"gated":[39],"recurrent":[40],"unit":[41],"relatively":[44],"large":[45],"size":[46],"of":[47,140,159],"hidden":[48],"units":[49],"is":[50,56,75,104,143],"utilized,":[51],"while":[52,149],"the":[53,78,112,138],"deployed":[57],"to":[58,145],"achieve":[59],"real-time":[60,152,167],"usage.":[62],"technique":[65],"(LP)":[70],"proposed,":[76],"where":[77,137],"LP":[79],"coefficients":[80],"are":[81],"estimated":[82],"in":[83],"manner.":[86],"Moreover,":[87],"loss":[90],"function":[91],"using":[92,155],"short-time":[93],"Fourier":[94],"transform":[95],"(STFT)":[96],"Gumbel":[102],"approximation":[103],"also":[105],"proposed.":[106],"The":[107],"experimental":[108],"results":[109],"demonstrate":[110],"that":[111],"proposed":[113],"generates":[116],"synthetic":[118],"speech":[119],"seen":[121],"unseen":[123],"speakers":[124,129],"and/or":[125],"language":[126],"300":[128],"training":[130,141],"data":[131],"including":[132,169],"clean":[133],"noisy/reverberant":[135],"conditions,":[136],"number":[139],"utterances":[142],"limited":[144],"60":[146],"per":[147],"speaker,":[148],"allowing":[150],"processing":[154],"single":[157],"core":[158],"$\\sim\\!$":[160,165],"2.1--2.7":[161],"GHz":[162],"CPU":[163],"0.57--0.64":[166],"factor":[168],"input/output":[170],"feature":[172],"extraction.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
