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Project 1 : Qualifying and Quantifying Noise from Different Types of Guns (Vehicles) Brad Keserich, Senior, Computer Engineering College of Engineering.

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Presentation on theme: "Project 1 : Qualifying and Quantifying Noise from Different Types of Guns (Vehicles) Brad Keserich, Senior, Computer Engineering College of Engineering."— Presentation transcript:

1 Project 1 : Qualifying and Quantifying Noise from Different Types of Guns (Vehicles) Brad Keserich, Senior, Computer Engineering College of Engineering and Applied Science; University of Cincinnati; Cincinnati, Ohio Dr. Dharma Agrawal, Professor, School of Computing Sciences and Informatics 1 Sponsored ByThe National Science Foundation Grant ID No.: DUE-0756921

2 Introduction 2 Sensor VROOOM!!!

3 Overview We will be investigating the sounds generated by different types of vehicles. The hope is to find features in the sounds that allow for a vehicle to be uniquely identified. 3

4 Goals Determine salient features in training data set for distinguishing between sound source classes Correctly identify the source classes given a new data set 4

5 Objectives Acquire a varied dataset of vehicle audio Determine salient features using modern techniques Implement and train a classifier Test classifier performance using new data 5

6 Feature Vectors 6 w1w2 w3w4w5 t wivi = f1 f2 : : : : : fr

7 Classification Training –Training set of feature vectors –Convert to Zero-mean truth set –Principle components (top k) Classifying –Project new vectors onto eigenbasis –Residuals = how likely its not in any class –Eigenbasis coefficients = Likelihood of a given class 7

8 Alternative Techniques Laplacian Eigenmapping –Non-linear variant of (PCA) –Maps onto manifolds Mel-Frequency Cepstrum –Models human hearing –Cepstrum voice detection 8

9 Performance Measures 9 Receiver operating characteristic (ROC) curve False positive rate True positive rate 1 1 0 00.5 Better Worse

10 Project Time Schedule 10 No.Task Wks. 4-5Wks. 6-7Wks. 8-9Wks. 10-11Wks. 12-13Wks. 14-15 456789101112131415 1Plan roadmap XX 2 Conduct literature survey XX X X X X X 3Acquire data O O O O O O 4Analyze data O O O O 5TinyOS Seminar O 6 Attend seminars, skill workshops, and submit reflective feedback X X X X X X 7Get lab access X X 8Develop classifier XX 9 Progress reports and presentations X X X X 0 Prepare final deliverables XX 1 Final deliverables: Powerpoint Tech Paper Poster NSF Report


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