Speech Processing AEGIS RET All-Hands Meeting Applications of Images and Signals in High Schools AEGIS RET All-Hands Meeting Florida Institute of Technology July 6, 2012

Contributors Dr. Veton Këpuska, Faculty Mentor, FIT vkepuska@fit.edu Jacob Zurasky, Graduate Student Mentor, FIT jzuraksy@my.fit.edu Becky Dowell, RET Teacher, BPS Titusville High dowell.jeanie@brevardschools.org

Motivation Timeline / Background – need to add this Difficulties Siri demo

Motivation Speech audio processing has increased in its usefulness. Applications Siri on iPhone 4S Automated telephone systems Voice transcription (e.g. dictation software) Hands-free computing (e.g., OnStar) Video games (e.g., XBOX Kinect) Military applications (e.g., aircraft control) Healthcare applications

Motivation Speech recognition requires speech to first be characterized by a set of “features”. Features are used to determine what words are spoken. Our project implements the feature extraction stage of a speech processing application.

Speech Recognition Front End: Pre-processing Back End: Recognition Speech Recognized speech Large amount of data. Ex: 256 samples Features Reduced data size. Ex: 13 features Front End – reduce amount of data for back end, but keep enough data to accurately describe the signal. Output is feature vector. 256 samples ------> 13 features Back End - statistical models used to classify feature vectors as a certain sound in speech

Front-End Processing of Speech Recognizer Pre-emphasis Window FFT Mel-Scale log IFFT

Speech Analysis Project Added GUI Allow user to record audio or input audio from a sound file Displays graph of the audio User can click on graph to select speech frame Processes speech frame and displays output for each state of processing Displays spectrogram

GUI Components

GUI Components Plotting Axes

Buttons GUI Components Plotting Axes

Future Work Improve GUI Audio Effects Noise Filtering

References Ingle, Vinay K., and John G. Proakis. Digital signal processing using MATLAB. 2nd ed. Toronto, Ont.: Nelson, 2007. Oppenheim, Alan V., and Ronald W. Schafer. Discrete-time signal processing. 3rd ed. Upper Saddle River: Pearson, 2010. Weeks, Michael. Digital signal processing using MATLAB and wavelets. Hingham,Mass.: Infinity Science Press, 2007.

Thank you! Questions?

Unit Plan