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dc.contributor.authorYang, Na
dc.contributor.authorBa, He
dc.contributor.authorCai, Weiyang
dc.contributor.authorSeyfettin Demirkol, Ilker
dc.contributor.authorHeinzelman, Wendi
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica
dc.date.accessioned2017-03-22T10:10:17Z
dc.date.available2017-03-22T10:10:17Z
dc.date.issued2014-08-27
dc.identifier.citationYang, N., Ba, H., Cai, W., Demirkol, I., Heinzelman, W. BaNa: a noise resilient fundamental frequency detection algorithm for speech and music. "IEEE transactions on audio speech and language processing", 27 Agost 2014, vol. 22, núm. 12, p. 1833-1848.
dc.identifier.issn1558-7916
dc.identifier.urihttp://hdl.handle.net/2117/102780
dc.description.abstractFundamental frequency (F0) is one of the essential features in many acoustic related applications. Although numerous F0 detection algorithms have been developed, the detection accuracy in noisy environments still needs improvement. We present a hybrid noise resilient F0 detection algorithm named BaNa that combines the approaches of harmonic ratios and Cepstrum analysis. A Viterbi algorithm with a cost function is used to identify the F0 value among several F0 candidates. Speech and music databases with eight different types of additive noise are used to evaluate the performance of the BaNa algorithm and several classic and state-of-the-art F0 detection algorithms. Results show that for almost all types of noise and signal-to-noise ratio (SNR) values investigated, BaNa achieves the lowest Gross Pitch Error (GPE) rate among all the algorithms. Moreover, for the 0 dB SNR scenarios, the BaNa algorithm is shown to achieve 20% to 35% GPE rate for speech and 12% to 39% GPE rate for music. We also describe implementation issues that must be addressed to run the BaNa algorithm as a real-time application on a smartphone platform.
dc.format.extent16 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
dc.subject.lcshAutomatic speech recognition
dc.subject.lcshSignal processing
dc.subject.lcshMusic
dc.subject.otherViterbi algorithm
dc.subject.otherCepstrum
dc.subject.otherFundamental frequency detection
dc.subject.otherHarmonics
dc.subject.otherNoise resilience
dc.titleBaNa: a noise resilient fundamental frequency detection algorithm for speech and music
dc.typeArticle
dc.subject.lemacReconeixement automàtic de la parla
dc.subject.lemacTractament del senyal
dc.subject.lemacMúsica
dc.contributor.groupUniversitat Politècnica de Catalunya. WNG - Grup de xarxes sense fils
dc.identifier.doi10.1109/TASLP.2014.2352453
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/document/6884780/
dc.rights.accessOpen Access
local.identifier.drac19790603
dc.description.versionPostprint (author's final draft)
local.citation.authorYang, N.; Ba, H.; Cai, W.; Demirkol, I.; Heinzelman, W.
local.citation.publicationNameIEEE transactions on audio speech and language processing
local.citation.volume22
local.citation.number12
local.citation.startingPage1833
local.citation.endingPage1848


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