Index of content:
Volume 121, Issue 1, January 2007
- ACOUSTICAL MEASUREMENTS AND INSTRUMENTATION 
121(2007); http://dx.doi.org/10.1121/1.2387130View Description Hide Description
The Volume-Unit (VU) meter, used in speech research prior to the advent of computers and modern signal processing methods, is described in signal processing terms. There are no known software implementations of this meter, which meet the 1954 ASA standard and provide the instantaneous needle level. Important speech applications will be explored, such as making comparisons of speech levels to earlier classic works, and measuringspeech levels using traditional methods on modern computers. It is our intention to make this venerable method of measuringspeech levels available once again. The VU meter is simulated and its properties are studied. A 1950s vintage and a recent vintage VU meter are studied by comparing the transient responses to tones and measurement of speech levels. Based on these measurements, a software VU meter (henceforth referred to as VUSOFT) is simulated, and verified. The method for reading the meter is explained, and simulated in software. The VU level for speech is shown to depend on the reading duration. The relationship between the root-mean-squared (rms) level of a signal and the VU level of a signal is determined, as a function of the meter-reading time.
121(2007); http://dx.doi.org/10.1121/1.2382748View Description Hide Description
An aberration estimation algorithm, previously developed in the frequency domain, is implemented in the time domain. The algorithm is used to estimate arrival time and amplitude fluctuations with signals from random scatterers. Simulations have been performed to investigate the variance of the estimates. Stability differences between the two implementations are also explored. Eight body wall models, emulating the human abdominal wall, were used for this purpose. The variance was investigated as a function of the number of independent scatterer realizations, used to obtain an estimate. Such signals may be acquired by imaging moving scatterers, e.g., blood or contrast agent. Alternatively they can be obtained by using different nonoverlapping beams from a sector/linear scan. The results show only minor differences between the two implementations with respect to stability. This means that the algorithm can be readily implemented in the time domain for real-time applications. The standard deviation of arrival time and amplitude fluctuation estimates decrease, when the number of independent signals increase. Using only one signal for estimation produces a relatively high standard deviation, but an iterative transmit-beam aberration correction scheme still converges to a properly corrected focus using between one and four transmit-beam iterations for the investigated aberrators.