Automatic Speech Recognition (ASR) still poses a problem to researchers. In particular, most ASR systems have not been able to fully handle adverse acoustic environments. Although a large number of modi cations have resulted in increased levels of performance robustness, ASR systems still fall short of human recognition ability in a large number of environments. A possible shortcoming of the ty...

This paper describes a method to visualize and localize the sound that is simulated within a virtual environment using beamforming. The use of an acoustic camera along with noise image software as a short introduction to beamforming method is demonstrated. Furthermore, the transition from the three-dimensional sound recording to the three-dimensional virtual acoustic mapping, visualization and ...

An extension of Jacobian Adaptation (JA) of HMMs for degraded speech recognition is presented in which appropriate set of initial models is selected from a number of initial-model sets designed for different noise environments. Based on the first order Taylor series approximation in the acoustic feature domain, JA adapts the acoustic model parameters trained in the initial noise environment A t...

Social interactions among individuals are often mediated through acoustic signals. If acoustic signals are consistent and related to an individual's personality, these consistent individual differences in signalling may be an important driver in social interactions. However, few studies in non-human mammals have investigated the relationship between acoustic signalling and personality. Here we ...

Concern has increased about the role of man-made noise in the marine environment. To address this, ONR has supported the development of the Effects of Sound on the Marine Environment (ESME) workbench. The initial Graphical User Interface was developed by NRL using Matlab with calls to FORTRAN implementations of acoustic propagation models. The acoustic modeling tools are mostly drawn from ONR’s...