Show simple item record

dc.contributor.authorHansen, John H. L.en_US
dc.contributor.authorNandwana, M. K.en_US
dc.contributor.authorShokouhi, N.en_US
dc.date.accessioned2018-08-20T16:19:50Z
dc.date.available2018-08-20T16:19:50Z
dc.date.created2017-04-27en_US
dc.date.issued2018-08-20
dc.identifier.issn0001-4966en_US
dc.identifier.urihttp://hdl.handle.net/10735.1/5982
dc.description.abstractScream is defined as sustained, high-energy vocalizations that lack phonological structure. Lack of phonological structure is how scream is identified from other forms of loud vocalization, such as "yell." This study investigates the acoustic aspects of screams and addresses those that are known to prevent standard speaker identification systems from recognizing the identity of screaming speakers. It is well established that speaker variability due to changes in vocal effort and Lombard effect contribute to degraded performance in automatic speech systems (i.e., speech recognition, speaker identification, diarization, etc.). However, previous research in the general area of speaker variability has concentrated on human speech production, whereas less is known about non-speech vocalizations. The UT-NonSpeech corpus is developed here to investigate speaker verification from scream samples. This study considers a detailed analysis in terms of fundamental frequency, spectral peak shift, frame energy distribution, and spectral tilt. It is shown that traditional speaker recognition based on the Gaussian mixture models-universal background model framework is unreliable when evaluated with screams. © 2017 Author(s).en_US
dc.description.sponsorship"This work was supported in part by the Air Force Research Laboratory under Contract No. FA8750-15-1-0205."en_US
dc.language.isoenen_US
dc.publisherAcoustical Society of Americaen_US
dc.relation.urihttp://dx.doi.org/10.1121/1.4979337en_US
dc.rightsCC BY 4.0 (Attribution)en_US
dc.rights©2017 The Authorsen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectLoudspeakersen_US
dc.subjectSpeechen_US
dc.subjectSpeech processing systemsen_US
dc.subjectSpeech perceptionen_US
dc.subjectSpeech Acousticsen_US
dc.titleAnalysis of Human Scream and Its Impact on Text-Independent Speaker Verificationen_US
dc.type.genrearticleen_US
dc.description.departmentErik Jonsson School of Engineering and Computer Scienceen_US
dc.description.departmentCenter for Robust Speech Systemsen_US
dc.identifier.bibliographicCitationHansen, J. H. L., M. K. Nandwana, and N. Shokouhi. 2017. "Analysis of human scream and its impact on text-independent speaker verification." Journal of the Acoustical Society of America 141(4), doi:10.1121/1.4979337en_US
dc.source.journalJournal of the Acoustical Society of Americaen_US
dc.identifier.volume141en_US
dc.identifier.issue4en_US
dc.contributor.utdAuthorHansen, John H. L.en_US
dc.contributor.utdAuthorNandwana, M. K.en_US
dc.contributor.utdAuthorShokouhi, N.en_US
dc.contributor.VIAF19968651 (Hansen, JHL)en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

CC BY 4.0 (Attribution)
Except where otherwise noted, this item's license is described as CC BY 4.0 (Attribution)