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Speaker And Gender Identification Using Bioacoustic Data Sets, Neenu Jose
Speaker And Gender Identification Using Bioacoustic Data Sets, Neenu Jose
Theses and Dissertations--Electrical and Computer Engineering
Acoustic analysis of animal vocalizations has been widely used to identify the presence of individual species, classify vocalizations, identify individuals, and determine gender. In this work automatic identification of speaker and gender of mice from ultrasonic vocalizations and speaker identification of meerkats from their Close calls is investigated. Feature extraction was implemented using Greenwood Function Cepstral Coefficients (GFCC), designed exclusively for extracting features from animal vocalizations. Mice ultrasonic vocalizations were analyzed using Gaussian Mixture Models (GMM) which yielded an accuracy of 78.3% for speaker identification and 93.2% for gender identification. Meerkat speaker identification with Close calls was implemented using Gaussian …
A Method For Non-Invasive, Automated Behavior Classification In Mice, Using Piezoelectric Pressure Sensors, Steven R. Gooch
A Method For Non-Invasive, Automated Behavior Classification In Mice, Using Piezoelectric Pressure Sensors, Steven R. Gooch
Theses and Dissertations--Electrical and Computer Engineering
While all mammals sleep, the functions and implications of sleep are not well understood, and are a strong area of investigation in the research community. Mice are utilized in many sleep studies, with electroencephalography (EEG) signals widely used for data acquisition and analysis. However, since EEG electrodes must be surgically implanted in the mice, the method is high cost and time intensive. This work presents an extension of a previously researched high throughput, low cost, non-invasive method for mouse behavior detection and classification. A novel hierarchical classifier is presented that classifies behavior states including NREM and REM sleep, as well …