A sophisticated, multi-channel data acquisition and processing system for high frequency noise research

A sophisticated, multi-channel computerized data acquisition and processing system was developed at the NASA LeRC for use in noise experiments. This technology, which is available for transfer to industry, provides a convenient, cost-effective alternative to analog tape recording for high frequency acoustic measurements. This system provides 32-channel acquisition of microphone signals with an analysis bandwidth up to 100 kHz per channel. Cost was minimized through the use of off-the-shelf components. Requirements to allow for future expansion were met by choosing equipment which adheres to established industry standards for hardware and software. Data processing capabilities include narrow band and 1/3 octave spectral analysis, compensation for microphone frequency response/directivity, and correction of acoustic data to standard day conditions. The system was used successfully in a major wind tunnel test program at NASA LeRC to acquire and analyze jet noise data in support of the High Speed Civil Transport (HSCT) program

Propfan Test Assessment (PTA): Flight test report

The Propfan Test Assessment (PTA) aircraft was flown to obtain glade stress and noise data for a 2.74m (9 ft.) diameter single rotation propfan. Tests were performed at Mach numbers to 0.85 and altitudes to 12,192m (40,000 ft.). The propfan was well-behaved structurally over the entire flight envelope, demonstrating that the blade design technology was completely adequate. Noise data were characterized by strong signals at blade passage frequency and up to 10 harmonics. Cabin noise was not so high as to preclude attainment of comfortable levels with suitable wall treatment. Community noise was not excessive

Convolutional neural network for breathing phase detection in lung sounds

We applied deep learning to create an algorithm for breathing phase detection in lung sound recordings, and we compared the breathing phases detected by the algorithm and manually annotated by two experienced lung sound researchers. Our algorithm uses a convolutional neural network with spectrograms as the features, removing the need to specify features explicitly. We trained and evaluated the algorithm using three subsets that are larger than previously seen in the literature. We evaluated the performance of the method using two methods. First, discrete count of agreed breathing phases (using 50% overlap between a pair of boxes), shows a mean agreement with lung sound experts of 97% for inspiration and 87% for expiration. Second, the fraction of time of agreement (in seconds) gives higher pseudo-kappa values for inspiration (0.73-0.88) than expiration (0.63-0.84), showing an average sensitivity of 97% and an average specificity of 84%. With both evaluation methods, the agreement between the annotators and the algorithm shows human level performance for the algorithm. The developed algorithm is valid for detecting breathing phases in lung sound recordings

Thinking Inside the Box: A New Integrated Approach to Mixed Music Composition and Performance

The Thinking Inside the Box project (TItB) seeks to address pragmatic concerns inherent to mixed music performance, and proposes ways to better consider the sound of the acoustic reality of the concert space at studio composition time. This is achieved through empirical investigation into subversive use of recent developments in hardware and software technologies. The primary concerns are (1) optimising the integration of live instruments and electroacoustic sound in the concert hall environment for both the performers and the public, by carefully choosing loudspeaker types and placement at commission time, and by avoiding sound reinforcement; (2) minimizing for studio composers the insitu trauma of the first live rendition of the piece, by bringing the concert hall acoustic environment into the studio composition process, using convolution reverb to reproduce in the studio the given loudspeaker setup through its impulse responses. This paper presents the conclusions of the project's early experiments in the form of three case study sets, and describes how this approach will be of use for any composer of mixed music

A singer's point of reference: baseline vocal measurements during study at a university

The careers of professional voice users depend a great deal on the quality and condition of their voices. Voice students in a university are training their voices for professional use. Vocal health and hygiene are of utmost importance. Often acoustic and aerodynamic measures of the voice are not obtained until after the student experiences vocal difficulties not due directly to technical issues. A record of the student's voice obtained when healthy is useful in evaluating the voice when it is in distress. This paper discusses the advantages to collecting and recording baseline vocal measurements while a student is studying voice. It also explains the kinds of vocal parameters which are most helpful in the evaluation, the instrumentation used to obtain the measurements, as well as the procedures and protocol used in obtaining them. Strategies for using the information and for setting up a system in a university to collect and record students' baseline measurements are also included