Sound field decomposition based on two-stage neural networks

A method for sound field decomposition based on neural networks is proposed. The method comprises two stages: a sound field separation stage and a single-source localization stage. In the first stage, the sound pressure at microphones synthesized by multiple sources is separated into one excited by each sound source. In the second stage, the source location is obtained as a regression from the sound pressure at microphones consisting of a single sound source. The estimated location is not affected by discretization because the second stage is designed as a regression rather than a classification. Datasets are generated by simulation using Green's function, and the neural network is trained for each frequency. Numerical experiments reveal that, compared with conventional methods, the proposed method can achieve higher source-localization accuracy and higher sound-field-reconstruction accuracy.Comment: 31 pages, 16 figure

Investigation of sweet spot radius of sound reconstruction system based on inverse filtering

International audienceSound field reconstruction techniques are very effective tools for a sound system of live-viewing or acoustical design in architecture. In the live-viewing system, listeners can enjoy highly realistic sound through the system. In addition, the system would allow acoustical designers to evaluate a sound field calculated in architectural spaces before their completion. There are several methods aiming at sound field reconstruction, such as Higher-order Ambisonics (HOA), Wave Field Synthesis (WFS), and Boundary Surface Control (BoSC). It is important to reconstruct a sound field within a broad region in order to allow a listener to look around or to move, or to allow multiple listeners to experience the sound field at the same time. To reconstruct a sound field in a broad region, it is necessary to employ lots of microphones and loudspeakers. It is becoming easier and less expensive to handle many devices due to the progress of computer technologies and network audio technologies. The reconstruction region of a sound field is called a sweet spot, which is defined as an area in which a normalized reconstructed error (NRE) would be smaller than 4%, for an example. HOA is a method to reconstruct a sound field using the spherical harmonics expansion. It is known that a radius of sweet spot in HOA is proportional to an expansion order. In the BoSC system, both sound pressure and particle velocity on the boundary surface of a reconstruction region are to be controlled using inverse filters to reconstruct a sound field. While the BoSC system aims to reconstruct a sound field in a region surrounded by boundary surface, some researchers suggest that a sweet spot would be formed outside of this controlled region. The authors numerically investigated the radius of sweet spot for the BoSC system which consisted of a spherical controlling surface and a spherical loudspeaker array. The spherical loudspeaker array and spherical microphone array were employed in the numerical simulation. The radius of the spherical loudspeaker array was 2.5 meters and the number of loudspeakers was 122. The loudspeakers were mounted at the vertices of the geodesic polyhedron. The number of microphones was varied from 16 to 256 and the radii of the microphone array was varied from 0.05 meters to 0.20 meters. The microphones were located at the positions calculated from the Fibonacci spiral. The results showed that the radii of the microphone array, within which the sound field would be reconstructed accurately in theory, do not affect the radii of sweet spot, but the number of the microphones could be related to the radii of sweet spot. Furthermore, the radii of sweet spot is inversely proportional to the frequency. These results indicated that the relation between the radii of sweet spot and the number of microphones in the BoSC system is likely parallel to that of the HOA system. In general, the BoSC system could be realized by simplified control of only sound pressures except for resonance frequencies of the corresponding internal Dirichlet problem. However, the results also suggested that this simplification could have an impact on the radius of sweet spot

Numerical simulation of transfer and attenuation characteristics of soft-tissue conducted sound originating from vocal tract

A non-audible murmur (NAM), a very weak speech sound produced without vocal cord vibration, can be detected by a special NAM microphone attached to the neck, thereby providing a new speech communication tool for functional speech disorders as well as human-to-machine and human-to-human interfaces with inaudible voice input for use with unimpaired. The NAM microphone is a condenser microphone covered with soft-silicone impression material that provides good impedance matching with the soft tissues of the neck. Because higher-frequency components are suppressed severely, however, the NAM detected with this device can be insufficiently clear. To improve NAM clarity, the mechanism of NAM production as well as the transfer characteristics of the NAM in soft neck tissues must be clarified. We have investigated sound propagation from the vocal tract to the neck surface, using a finite difference time domain method and a head model based on magnetic resonance imaging scans. Numerical results show that, compared to air-conducted sound detected in front of a mouth, soft-tissue-conducted sound attenuates 50 dB at 1 kHz, which consists of 30 dB full-range attenuation due to air-to-soft-tissues transmission loss and -10 dB/octave spectral decay due to a propagation loss in soft tissues. The decay agrees well with the spectral characteristics of the measured NAM. (C) 2008 Elsevier Ltd. All rights reserved.ArticleAPPLIED ACOUSTICS. 70(3):469-472 (2009)journal articl

Deformation behavior and acting earth pressure of three-hinge precast arch culvert in construction process

The three-hinge precast arch culvert consists of two segmental precast units and three hinge points. It harnesses the passive resistance of an embankment by permitting deflection, resulting in a mechanically stable structure. However, the design of the three-hinge precast arch culvert differs from that of a conventional culvert, prompting the mechanical behavior of the culvert to become an important issue. In this study, therefore, 1/5 scale model tests were conducted on a three-hinge precast arch culvert to measure the changes in the inside width and earth pressure acting on the culvert at each step in order to investigate the culvert’s mechanical behavior at each construction stage. Moreover, the deflection measurement of the culvert was obtained at the in-situ construction site. The results indicate that the arch members were displaced according to the embankment depth in a similar manner to the design load. Therefore, the horizontal earth pressure, which was larger than the earth pressure at rest, acted on the culvert at the end of its construction

Affect of reality monitoring in obsessive-compulsive checker

Reality monitoring has been considered as a cause of a check compulsion, which is one dominantsymptom in obsessive-compulsive disorder (OCD). However, the previous studies could not confirm confusionsof reality monitoring in OCD checkers but found decrements of the confidence for memorizing (McNally& Kohlbeck, 1993; Constant, For, Franklin & Mathes, 1995). Since the previous studies had many problemsconcerning to the task and the hedonic value of stimuli, they could not discuss confusions of reality monitoringof OCD checkers sufficiently. The present study aimed to examine the reality monitoring of OCD checkers byusing an incidental learning task, which hedonic values of stimuli were experimentally controlled (neutral,negative and positive). As results, confusions of the reality monitoring of OCD were found in false alarms ofneutral and positive words. However, any decrement of the confidence for memorizing was not found. Theseresults were inconsistent with the finding of the previous studies

Silent-speech enhancement using body-conducted vocal-tract resonance signals

The physical characteristics of weak body-conducted vocal-tract resonance signals called non-audible murmur (NAM) and the acoustic characteristics of three sensors developed for detecting these signals have been investigated. NAM signals attenuate 50 dB at 1 kHz; this attenuation consists of 30-dB full-range attenuation due to air-to-body transmission loss and 10 dB/octave spectral decay due to a sound propagation loss within the body. These characteristics agree with the spectral characteristics of measured NAM signals. The sensors have a sensitivity of between 41 and 58 dB [V/Pa] at I kHz, and the mean signal-to-noise ratio of the detected signals was 15 dB. On the basis of these investigations, three types of silent-speech enhancement systems were developed: (1) simple, direct amplification of weak vocal-tract resonance signals using a wired urethane-elastomer NAM microphone, (2) simple, direct amplification using a wireless urethane-elastomer-duplex NAM microphone, and (3) transformation of the weak vocal-tract resonance signals sensed by a soft-silicone NAM microphone into whispered speech using statistical conversion. Field testing of the systems showed that they enable voice impaired people to communicate verbally using body-conducted vocal-tract resonance signals. Listening tests demonstrated that weak body-conducted vocal-tract resonance sounds can be transformed into intelligible whispered speech sounds. Using these systems, people with voice impairments can re-acquire speech communication with less effort. (C) 2009 Elsevier B.V. All rights reserved.ArticleSPEECH COMMUNICATION. 52(4):301-313 (2010)journal articl

Estimation of the low-frequency components of the head-related transfer functions of animals from photographs

Reliable animal head-related transfer function (HRTF) estimation procedures are needed for several practical applications. For example, to investigate the neuronal mechanisms of sound localization using virtual acoustic spaces, or to have a quantitative description of the di erent localization cues available to a given animal species. Here two established techniques are combined to estimate an animal's HRTF from photographs by taking into account as much morphological detail as possible. The rst step of the method consists in building a 3D-model of the animal from pictures taken with a standard camera. The HRTFs are then estimated by means of a rapid boundary-element-method implementation. This combined method is validated on a taxidermist model of a cat by comparing binaural and monaural localization cues extracted from estimated and measured HRTFs. It is shown that it provides a reliable way to estimate low-frequency HRTF, which are di cult to obtain with standard acoustical measurements procedures because of re ections.ERC StG 24013