| Title: | Acoustic Gender and Age Classification as an Aid to Human–Computer Interaction in a Smart Home Environment |
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| Authors: | ID Vlaj, Damjan (Author)
ID Žgank, Andrej (Author) |
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| Files: |  mathematics-11-00169.pdf (2,07 MB)
MD5: CAC05ED299DCE1474E57DEED4D15A735
 https://www.mdpi.com/2227-7390/11/1/169
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
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| Abstract: | The advanced smart home environment presents an important trend for the future of human wellbeing. One of the prerequisites for applying its rich functionality is the ability to differentiate between various user categories, such as gender, age, speakers, etc. We propose a model for an efficient acoustic gender and age classification system for human–computer interaction in a smart home. The objective was to improve acoustic classification without using high-complexity feature extraction. This was realized with pitch as an additional feature, combined with additional acoustic modeling approaches. In the first step, the classification is based on Gaussian mixture models. In thesecond step, two new procedures are introduced for gender and age classification. The first is based on the count of the frames with the speaker’s pitch values, and the second is based on the sum of the frames with pitch values belonging to a certain speaker. Since both procedures are based on pitch values, we have proposed a new, effective algorithm for pitch value calculation. In order to improve gender and age classification, we also incorporated speech segmentation with the proposed voice activity detection algorithm. We also propose a procedure that enables the quick adaptation of the classification algorithm to frequent smart home users. The proposed classification model with pitch values has improved the results in comparison with the baseline system. |
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| Keywords: | acoustic classification, acoustic signal processing, Gaussian mixture model, pitch analysis, smart home |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 24.11.2022 |
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| Article acceptance date: | 26.12.2022 |
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| Publication date: | 29.12.2022 |
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| Publisher: | MDPI |
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| Year of publishing: | 2023 |
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| Number of pages: | 22 str. |
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| Numbering: | Vol. 11, no. 1 |
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| PID: | 20.500.12556/DKUM-86550  |
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| UDC: | 621.39 |
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| ISSN on article: | 2227-7390 |
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| COBISS.SI-ID: | 136469251 |
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| DOI: | 10.3390/math11010169 |
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| Publication date in DKUM: | 11.12.2023 |
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| Views: | 663 |
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| Downloads: | 39 |
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| Metadata: |    |
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| Categories: | Misc.
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