Travis Doll

Bio:


I am a fourth year graduate student in the Electrical and Computer Engineering department at Drexel University. Currently, I am in pursuit of a Ph.D. in Electrical Engineering with a focus in digital signal processing. In the summer prior to my fourth year, I was appointed an adjunct professor position as I was the instructor for an undergraduate Java programming course (ECE-203 Programming for Engineers). At the conclusion of the summer, I was awarded a position with the Engineering Teaching Fellowship at Drexel where I co-teach four lab sections of an undergraduate introductory to engineering course (ENGR-101) with several Drexel faculty.

During my second and third years as a graduate student, I was awarded a fellowship with the NSF GK-12 program at Drexel. As a participant in this program, I traveled to Girard Academic Music Program in south Philadelphia during my second year and Martha Washington Elementary in west Philadelphia during my third year twice a week to utilize Electrical Engineering to highlight linkages between 7th and 8th grade math and science concepts and everyday technologies. More information about the lessons and activities I created as part of the program can be found in a section below.

In my first year at Drexel, I was both a teaching assistant and a research assistant in the Electrical and Computer Engineering department. As a teaching assistant I work with an undergraduate class on digital logic design. As a research assistant I performed research in the MET-lab.

In 2006, I graduated from Dickinson College with a B.S. in Computer Science. While at Dickinson, I studied computer science with an emphasis in math and physics. In addition, I held a position as a teaching assistant for two years in the Computer Science department. Aside from academics, I was a member of the varsity Men's Basketball Team for the duration of my undergraduate career.


Education:


  • PhD Electrical Engineering, Drexel University expected June 2010
  • MS Electrical Engineering, Drexel University 2008
  • BS Computer Science, Dickinson College 2006


Research Interests:


  • Source and filter estimation
  • Sparse audio coding
  • Speaker identification and verification
  • Educational gaming
  • Engineering education


Current Research:


Cocktail Party Game* - An online collaborative activity that aims to educate students in grades K-12 about sound and acoustic concepts such as the cocktail party problem (sound source isolation within mixtures). Also, the activity provides a method for the collection of psychoacoustic data on human auditory perception.
*-This activity is under constant development and may not be available from time to time.


Societies:


  • Eta Kappa Nu, Electrical and Computer Engineering Honor Society
  • GK-12 Fellow, National Science Foundation (NSF) Teaching Fellowship
  • Upsilon Pi Epsilon, International Honor Society for the Computing and Information Disciplines
  • IEEE member


Developed Lessons from NSF GK-12 Program:



Presentations:


  • T. M. Doll, R. Migneco, and Y. E. Kim, "Web-based sound and music games with activities for STEM education," Presentation at International IEEE Consumer Electronics Society's Games Innovations Conference, 2009. [slides PDF] [slides QuickTime]

  • R. Migneco, T. M. Doll, J. J. Scott, C. Hahn, P. J. Diefenbach, and Y. E. Kim, "An audio processing library for game development in Flash," Presentation at International IEEE Consumer Electronics Society's Games Innovations Conference, London, England, 2009. [slides PDF] [slides QuickTime]

  • Y. E. Kim and T. M. Doll, "Employing sparsity for joint sound source & acoustic channel estimation," Presentation at International Conference on Machine Learning Workshop on Sparse Methods for Music Audio, Montreal, Canada, 2009. [slides PDF] [slides QuickTime]

Presented Posters:


An Audio DSP Toolkit for Rapid Application Development in Flash - MMSP 2009


The Adobe Flash platform has become the de facto standard for developing and deploying media rich web applications and games. The relative ease-of-development and cross-platform architecture of Flash enables designers to rapidly prototype graphically rich interactive applications, but comprehensive support for audio and signal processing has been lacking. ActionScript, the primary development language used for Flash, is poorly suited for DSP algorithms. To address the inherent challenges in the integration of interactive audio processing into Flash-based applications, we have developed the DSP Audio Toolkit for Flash (DATF), which offers significant performance improvements over algorithms implemented in Java or ActionScript. By developing this toolkit, we hope to open up new possibilities for Flash applications and games, enabling them to utilize real-time audio processing as a means to drive gameplay and improve the experience of the end user.

Hide & Speak: An Online Game for K-12 Education and Psychoacoustic Data Collection - Drexel University Research Day 2009


Online collaborative game-based activities have been demonstrated to be effective supplemental tools for mathematics and science education, particularly for younger students in grades K-12. Such educational activities provide assistance in bridging the gap between abstract classroom concepts and real-world applications. I have developed a game, Hide & Speak, that allows students to explore aspects of different acoustical concepts through an interactive room environment simulator. Also inspired by recent work that utilize games to aid in solving difficult computational problems, Hide & Speak facilitates the collection of data on human auditory perception. Analysis of the data may lead to better models of the human auditory system and ultimately better-performing algorithms in speech related tasks.

Online Activities for Music Information and Acoustics Education and Psychoacoustic Data Collection - ISMIR 2008


Online collaborative activities provide a powerful platform for the collection of psychoacoustic data on the perception of audio and music from a very large number of subjects. Furthermore, these activities can be designed to simultaneously educate users about aspects of music information and acoustics, particularly younger students in grades K-12. We have created prototype interactive activities illustrating aspects of two different sound and acoustics concepts: musical instrument timbre and the cocktail party problem (sound source isolation within mixtures). These activities also provide a method of collecting perceptual data related to these problems with a range of parameter variation that is difficult to achieve for large subject populations using traditional psychoacoustic evaluation. We present preliminary data from a pilot study where middle school students were engaged with the two activities to demonstrate the potential benefits as a platform for education and data collection.

Online Acoustic Simulations for Education and Listener Evaluations - Drexel University Research Day 2008


Online collaborative activities provide a powerful platform for the collection of psychoacoustic data on the perception of audio and music from a very large numbers of subjects. Furthermore, these activities can be designed to simultaneously educate users about aspects of music information and acoustics, particularly for younger students in grades K-12.

Joint Iterative Multi-Speaker Identification and Source Separation Using Expectation Propagation - WASPAA 2007


This research examines the "cocktail party" problem which is generally described as the brain's ability to differentiate between multiple sounds that occur at the same time. Our system follows this idea by iteratively attempting to estimate the speech coming from each person’s mouth in a mixture of voices and identify those individuals speaking in the room. Through iterations the system attempts to gain more information about the speakers for better estimation and identification performance. This collaborative project is guided by Dr. John MacLaren Walsh.

Automatic Speaker Identification - Drexel University Research Day 2007


The voice contains many distinguishing characteristics that enable a person’s speech to be implemented as a method of identification. This research investigates the performance of the voice as a biometric identifier in single speaker and two speaker instantaneous mixture configurations. The performance of both configurations were tested using both Kullback-Leibler divergence and Neyman-Pearson detection classification methods.


Publications & Abstracts:


  • T. M. Doll, R. Migneco, J. J. Scott, and Y. E. Kim, "An audio DSP toolkit for rapid application development in Flash," IEEE International Workshop on Multimedia Signal Processing, 2009. [PDF]

  • R. Migneco, T. M. Doll, J. J. Scott, C. Hahn, P. J. Diefenbach, and Y. E. Kim, "An audio processing library for game development in Flash," in International IEEE Consumer Electronics Society's Games Innovations Conference, 2009. [PDF]

  • T. M. Doll, R. Migneco, and Y. E. Kim, "Web-based sound and music games with activities for STEM education," in International IEEE Consumer Electronics Society's Games Innovations Conference, 2009. [PDF]

  • Y. E. Kim and T. M. Doll, “Employing Sparsity for Joint Sound Source & Acoustic Channel Estimation,” presented at International Conference on Machine Learning: Workshop on Sparse Methods for Music Audio, 2009. [PDF]

  • Y. E. Kim, T. M. Doll, and R. Migneco, "Collaborative online activities for acoustics education and psychoacoustic data collection," in IEEE Transactions on Learning Technologies, 2009. [PDF]

  • T. M. Doll, R. Migneco, and Y. E. Kim, "Online activities for music information and acoustics education and psychoacoustic data collection," in Proceedings International Conference on Music Information Retrieval, 2008. [PDF]

  • Y. E. Kim, J. M. Walsh, and T. M. Doll, "Comparison of a joint iterative method for multiple speaker identification with sequential blind source separation and speaker identification," in Proceedings of the ICSA Odyssey Workshop on Speaker and Language Recognition, 2008. [PDF]

  • J. M. Walsh, Y. E. Kim, and T. M Doll, "Joint iterative multi-speaker identification and source separation using expectation propagation," in IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2007. [PDF]