SPeech ACoustic (SPAC): A novel tool for speech feature extraction and classification

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dc.contributor.authorOzseven, Turgut
dc.contributor.authorDugenci, Muharrem
dc.date.accessioned2024-09-29T15:54:56Z
dc.date.available2024-09-29T15:54:56Z
dc.date.issued2018
dc.departmentKarabük Üniversitesien_US
dc.description.abstractBackground and objective: The acoustic analysis, an objective evaluation method, is used to determine the descriptive attributes of the voices. Although there are many tools available in the literature for acoustic analysis, these tools are separated by features such as ease of use, visual interface, and acoustic parameter library. In this work, we have developed a new toolbox named SPAC for extracting and simulating attributes from speech files. Methods: SPAC has a modular structure and user-friendly interface, which will make up for the shortcomings of existing vehicles. In addition, modules can be used independently of each other. With SPAC, about 723 attributes can be extracted from each voice file in 9 categories. A validation test was applied to verify the validity of the toolbox-derived attributes. When the validation test was performed, the attributes obtained with Praat and OpenSMILE were grouped as standard, the attributes obtained with SPAC as test data, and the general differences between the attributes were evaluated with mean square error and mean percentage error. In another method used for verification, the classification performance is tested using the SPAC-derived attributes for classification. Results: According to the validation test results, SPAC attributes differ between 0.2% and 9.7% compared to other toolboxes. According to the results of the classification test, the SPAC attribute clusters can identify each class and the classification success varies between 1% and 3% according to the attributes obtained from other toolboxes. As a result, the attributes obtained with SPAC accurately describe the voice data. Conclusions: SPAC's superiority over existing toolboxes is that it has an easy-to-use user-friendly interface, it is modular, allows graphical representation of results, includes classification module and allows to work with SPAC data or data obtained from different toolboxes. In addition, operations performed with other tools can be performed more easily with SPAC.en_US
dc.identifier.doi10.1016/j.apacoust.2018.02.009
dc.identifier.endpage8en_US
dc.identifier.issn0003-682X
dc.identifier.issn1872-910X
dc.identifier.scopus2-s2.0-85042105860en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1016/j.apacoust.2018.02.009
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4371
dc.identifier.volume136en_US
dc.identifier.wosWOS:000430764500001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofApplied Acousticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSpeech feature extractionen_US
dc.subjectSpeech classificationen_US
dc.subjectSpeech toolboxen_US
dc.subjectSpeech processing toolboxen_US
dc.titleSPeech ACoustic (SPAC): A novel tool for speech feature extraction and classificationen_US
dc.typeArticleen_US

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