Scene analysis in the natural environment

The problem of scene analysis has been studied in a number of different fields over the past decades. These studies have led to a number of important insights into problems of scene analysis, but not all of these insights are widely appreciated. Despite this progress, there are also critical shortcomings in current approaches that hinder further progress. Here we take the view that scene analysis is a universal problem solved by all animals, and that we can gain new insight by studying the problems that animals face in complex natural environments. In particular, the jumping spider, songbird, echolocating bat, and electric fish, all exhibit behaviors that require robust solutions to scene analysis problems encountered in the natural environment. By examining the behaviors of these seemingly disparate animals, we emerge with a framework for studying analysis comprising four essential properties: 1) the ability to solve ill-posed problems, 2) the ability to integrate and store information across time and modality, 3) efficient recovery and representation of 3D scene structure, and 4) the use of optimal motor actions for acquiring information to progress towards behavioral goals

Investigating the build-up of precedence effect using reflection masking

The auditory processing level involved in the build‐up of precedence [Freyman et al., J. Acoust. Soc. Am. 90, 874–884 (1991)] has been investigated here by employing reflection masked threshold (RMT) techniques. Given that RMT techniques are generally assumed to address lower levels of the auditory signal processing, such an approach represents a bottom‐up approach to the buildup of precedence. Three conditioner configurations measuring a possible buildup of reflection suppression were compared to the baseline RMT for four reflection delays ranging from 2.5–15 ms. No buildup of reflection suppression was observed for any of the conditioner configurations. Buildup of template (decrease in RMT for two of the conditioners), on the other hand, was found to be delay dependent. For five of six listeners, with reflection delay=2.5 and 15 ms, RMT decreased relative to the baseline. For 5‐ and 10‐ms delay, no change in threshold was observed. It is concluded that the low‐level auditory processing involved in RMT is not sufficient to realize a buildup of reflection suppression. This confirms suggestions that higher level processing is involved in PE buildup. The observed enhancement of reflection detection (RMT) may contribute to active suppression at higher processing levels

Symphony: Localizing Multiple Acoustic Sources with a Single Microphone Array

Sound recognition is an important and popular function of smart devices. The location of sound is basic information associated with the acoustic source. Apart from sound recognition, whether the acoustic sources can be localized largely affects the capability and quality of the smart device's interactive functions. In this work, we study the problem of concurrently localizing multiple acoustic sources with a smart device (e.g., a smart speaker like Amazon Alexa). The existing approaches either can only localize a single source, or require deploying a distributed network of microphone arrays to function. Our proposal called Symphony is the first approach to tackle the above problem with a single microphone array. The insight behind Symphony is that the geometric layout of microphones on the array determines the unique relationship among signals from the same source along the same arriving path, while the source's location determines the DoAs (direction-of-arrival) of signals along different arriving paths. Symphony therefore includes a geometry-based filtering module to distinguish signals from different sources along different paths and a coherence-based module to identify signals from the same source. We implement Symphony with different types of commercial off-the-shelf microphone arrays and evaluate its performance under different settings. The results show that Symphony has a median localization error of 0.694m, which is 68% less than that of the state-of-the-art approach

Adaptive echolocation and flight behaviors in free-flying bats, Eptesicus fuscus

Echolocating bats emit ultrasonic sonar pulses and listen to returning echoes, which are reflected from targets or obstacles, to probe their surroundings. Their biological sonar system is well-developed and highly adaptive to the dynamic acoustic environment. Bats are also agile flyers and they can modify their flight behavior in order to capture insects efficiently. Adaptable echolocation and flight behaviors evolved in bats in response to environmental demands. This study employed changes in the external ear of bats and in the acoustic environment to examine how the big brown bat, Eptesicus fuscus, modifies its echolocation call design and flight patterns to cope with these new experimental conditions. Study one investigated the influences of changes in sound localization cues on prey capture behavior. The tragus, which is part of the external ear, is believed to contribute to sound localization in the vertical plane. Deflecting the tragus affected prey capture performance of the bat, but it adapted to this manipulation by adjusting its flight behavior. The tragus-deflected bat tended to attack the prey item from above and show lower tangential velocity and larger bearing from the side, compared with its flight pattern in the tragus intact conditions. The bat did not change its echolocation call design in the tragus-deflected condition. Study two paired two bats together and allowed them to perform a prey capture task in a large flight room. Echolocating bats showed two adaptive strategies in their echolocation behavior when flying with another conspecific. The bat either stopped vocalizing or increased its difference in call design from the other bat. In addition, one bat tended to follow another bat when flying together and antagonistic behavior was found in male-male and female-male pairs. The pursuit strategy the bat uses to track another bat is different from the strategy it uses to capture flying insects. This thesis confirms that the big brown bat's echolocation and flight behaviors are highly adaptable and describes several strategies the bat employs to cope with changes in sound localization cues and conspecific interference