University of Pittsburgh
June 11, 2002

Fact Sheet: Pitt Papers at the Acoustical Society of America Conference

Contact:  412-624-4147

June 6, 2002

PITTSBURGH—The following University of Pittsburgh papers are being presented at the Acoustical Society of America's Conference in Pittsburgh, through June 7. The descriptions are followed by the paper titles and ASA identification numbers. All researchers are available for interviews both during and after the conference.



Behavioral studies have demonstrated the effectiveness of feedback training in helping the brain discriminate between two sounds, but why is it successful? Are regions of the brain that are reward-related recruited to support learning? Julie Fiez, assistant professor of psychology and neuroscience at Pitt, is using the Japanese perception of /r/ versus /l/ as a model to explore how the brain perceives and discriminates between words like "rock" and "lock," pinpointing responsive areas in the brain with functional magnetic resonance imaging. Neuroimaging studies of phonetic category learning (2pSC2)


How does the human brain differentiate between a stranger's voice and that of a friend, or perceive a male voice from a female one? Some scientists say there is one prototype stored in the brain against which all other voices are measured. To support this theory, a group of men and women rated recordings of male and female voices. Results indicate that perceptions are complex and based on the interaction of pronunciation with the gender of the listener as well as that of the speaker. John Mullennix, associate professor and chairperson of the Department of Psychology, University of Pittsburgh at Johnstown, and research assistants Brian Spisak, Kelly Moro, and Jessica Will, along with Lynn Farnsworth from Wayne State University, will discuss the findings. Typicality ratings of male and female voices (4aSC21).



Harmonica players have a close relationship with their instruments. Because of the short distance between the player and the instrument's reed, even slight changes in the performer's mouth can dramatically affect the sound produced. Three Pitt researchers—James Antaki, M.D., assistant professor of surgery, assistant professor of mechanical engineering, and director of artificial heart research; Henry Bahnson, M.D., chairman emeritus, Department of Surgery; and Greg Burgreen, research assistant professor, Department of Surgery—present the results of x-ray, ultrasound, and laryngoscopic imaging studies in humans. Acoustic coupling between oral tract and diatonic harmonica: Recent observations (2pMUa7)


Matching an untrained singing voice to an existing database presents problems because the novice singer lacks precise pitch and timing. Mark Kahrs, visiting associate professor of electrical engineering at Pitt, describes an experimental system that searches for a match between a singer's input and a library of songs. An algorithm using dynamic time warping successfully accommodates pitch errors more than

95 percent of the time, but errors in meter cause problems even for very dissimilar songs. Matching untrained singers using dynamic time warping (4pMU3).

Rocket Science


Experimental and analytical methods were used to examine the noise transmission properties of a novel composite structure being evaluated by the Air Force Research Laboratory for rocket launch firings. In addition, ways to reduce the noise transmission though this structure by packing fill materials into the wall chambers are being investigated. Jeffrey S. Vipperman, assistant professor of mechanical engineering at Pitt and graduate research assistant Deyu Li will present the findings. Investigation of The Sound Transmission Behavior of a Chamber Core Cylinder (3aSAa4).



Draglines are extremely large and powerful machines that remove the earth covering a surface coal seam. Sound measurements were conducted and used to create noise-level contour plots for several different draglines, which revealed sound levels as high as 107 decibels. These "noise maps" indicate which are the noisiest locations and show which equipment makes the most noise. Researchers Jeffrey S. Vipperman, assistant professor of mechanical engineering at Pitt, and Eric R. Bauer from the National Institute for Occupational Safety and Health (NIOSH), Pittsburgh Research Lab, present the results of a survey of eight above-ground operations to determine the sources of mining noise and recommendations for mitigation. Dragline noise survey (1pNS5).


Significant hearing loss has been observed in miners, requiring that noise levels generated by mining equipment be reduced if possible. Successfully quieting equipment depends upon understanding the physics of noise generation and transmission. In this project, two types of sophisticated signal processing techniques are used to determine: 1) what parts of a coal conveyor generate the most noise; 2) how the noise propagates to where the miner would stand; and 3) what frequencies the noise contains. Pitt researchers John P. Homer, graduate research assistant, and Jeffrey S. Vipperman, assistant professor of mechanical engineering, join Efrem R. Reeves from the National Institute for Occupational Safety and Health to evaluate a chain conveyor for structure-borne and air-borne noise paths. Recommendations for devices to reduce noise to within regulatory guidelines resulted from the research. Identification and classification of noise sources in a chain conveyor (1pNS6)


Mining environments are plagued with difficulties regarding noise measurements, including harsh environment, potentially explosive gases, complex worker tasks, variable shift lengths, moving equipment, changing sound environment as coal is removed, multiple noise sources, and unexpected downtime. These issues will be illustrated along with ways to mitigate their effects. Researchers Jeffrey S. Vipperman, assistant professor of mechanical engineering at Pitt, and Eric R. Bauer from NIOSH explore the factors that make measuring noise problematic. Issues include constantly moving equipment, changing work environments, confined spaces, varying production rates, multiple noise sources, and electronic permissibility of instrumentation. Problems associated with noise measurements in the mining industry (1pNS4)