A Real-Time Smartphone App for Unsupervised Noise Classification In Realistic Audio Environments

dc.contributor.authorAlamdari, Nasim
dc.contributor.authorKehtarnavaz, Nasser
dc.contributor.utdAuthorAlamdari, Nasim
dc.contributor.utdAuthorKehtarnavaz, Nasser
dc.date.accessioned2020-07-23T21:54:54Z
dc.date.available2020-07-23T21:54:54Z
dc.date.issued2019-03-07
dc.descriptionDue to copyright restrictions and/or publisher's policy full text access from Treasures at UT Dallas is limited to current UTD affiliates (use the provided Link to Article).
dc.description.abstractThis paper presents a real-time unsupervised noise classifier smartphone app which is designed to operate in realistic audio environments. This app addresses the two limitations of a previously developed smartphone app for unsupervised noise classification. A voice activity detection is added to separate the presence of speech frames from noise frames and thus to lower misclassifications when operating in realistic audio environments. In addition, buffers are added to allow a stable operation of the noise classifier in the field. The unsupervised noise classification is achieved by fusing the decisions of two adaptive resonance theory unsupervised classifiers running in parallel. One classifier operates on subband features and the other operates on mel-frequency spectral coefficients. The results of field testing indicate the effectiveness of this unsupervised noise classifier app when used in realistic audio environments.
dc.description.departmentErik Jonsson School of Engineering and Computer Science
dc.description.sponsorshipNational Institute of the Deafness and Other Communication Disorders (NIDCD) of the National Institutes of Health (NIH) under the award number 1R01DC015430-01.
dc.identifierhttps://dx.doi.org/10.1109/ICCE.2019.8662052
dc.identifier.bibliographicCitationAlamdari, N., and N. Kehtarnavaz. 2019. "A Real-Time Smartphone App for Unsupervised Noise Classification in Realistic Audio Environments." 2019 IEEE International Conference on Consumer Electronics (ICCE): 1-5, doi: 10.1109/ICCE.2019.8662052
dc.identifier.issn2158-3994
dc.identifier.urihttps://hdl.handle.net/10735.1/8734
dc.language.isoen
dc.publisherIEEE
dc.rights©2019 IEEE
dc.source.journal2019 IEEE International Conference on Consumer Electronics (ICCE)
dc.subjectComputer science
dc.subjectEngineering
dc.subjectSmartphones
dc.subjectSpeech processing systems
dc.subjectGraphical user interfaces (Computer systems)
dc.subjectPipelines—Communication systems
dc.titleA Real-Time Smartphone App for Unsupervised Noise Classification In Realistic Audio Environments
dc.type.genrearticle

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