271 research outputs found

    Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action

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    Egelhaaf M, Boeddeker N, Kern R, Kurtz R, Lindemann JP. Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action. Frontiers in Neural Circuits. 2012;6:108.Insects such as flies or bees, with their miniature brains, are able to control highly aerobatic flight maneuvres and to solve spatial vision tasks, such as avoiding collisions with obstacles, landing on objects, or even localizing a previously learnt inconspicuous goal on the basis of environmental cues. With regard to solving such spatial tasks, these insects still outperform man-made autonomous flying systems. To accomplish their extraordinary performance, flies and bees have been shown by their characteristic behavioral actions to actively shape the dynamics of the image flow on their eyes ("optic flow"). The neural processing of information about the spatial layout of the environment is greatly facilitated by segregating the rotational from the translational optic flow component through a saccadic flight and gaze strategy. This active vision strategy thus enables the nervous system to solve apparently complex spatial vision tasks in a particularly efficient and parsimonious way. The key idea of this review is that biological agents, such as flies or bees, acquire at least part of their strength as autonomous systems through active interactions with their environment and not by simply processing passively gained information about the world. These agent-environment interactions lead to adaptive behavior in surroundings of a wide range of complexity. Animals with even tiny brains, such as insects, are capable of performing extraordinarily well in their behavioral contexts by making optimal use of the closed action-perception loop. Model simulations and robotic implementations show that the smart biological mechanisms of motion computation and visually-guided flight control might be helpful to find technical solutions, for example, when designing micro air vehicles carrying a miniaturized, low-weight on-board processor

    Jointly optimal denoising, dereverberation, and source separation

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    This paper proposes methods that can optimize a Convolutional BeamFormer (CBF) for jointly performing denoising, dereverberation, and source separation (DN+DR+SS) in a computationally efficient way. Conventionally, cascade configuration composed of a Weighted Prediction Error minimization (WPE) dereverberation filter followed by a Minimum Variance Distortionless Response beamformer has been usedas the state-of-the-art frontend of far-field speech recognition, however, overall optimality of this approach is not guaranteed. In the blind signal processing area, an approach for jointly optimizing dereverberation and source separation (DR+SS) has been proposed, however, this approach requires huge computing cost, and has not been extended for application to DN+DR+SS. To overcome the above limitations, this paper develops new approaches for jointly optimizing DN+DR+SS in a computationally much more efficient way. To this end, we first present an objective function to optimize a CBF for performing DN+DR+SS based on the maximum likelihood estimation, on an assumption that the steering vectors of the target signals are given or can be estimated, e.g., using a neural network. This paper refers to a CBF optimized by this objective function as a weighted Minimum-Power Distortionless Response (wMPDR) CBF. Then, we derive two algorithms for optimizing a wMPDR CBF based on two different ways of factorizing a CBF into WPE filters and beamformers. Experiments using noisy reverberant sound mixtures show that the proposed optimization approaches greatly improve the performance of the speech enhancement in comparison with the conventional cascade configuration in terms of the signal distortion measures and ASR performance. It is also shown that the proposed approaches can greatly reduce the computing cost with improved estimation accuracy in comparison with the conventional joint optimization approach.Comment: Submitted to IEEE/ACM Trans. Audio, Speech, and Language Processing on 12 Feb 2020, Accepted to IEEE/ACM Trans. Audio, Speech, and Language Processing on 14 July 202

    Report: 25 Years of Marian Apostolate

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    A report on the Marian Center in San Francisco by Fr. Alfred Boeddeker, O.F.M. outlining the Center\u27s local, national, and international activities between 1950 and 1975. Reproduced typescript

    Once more Diarization: Improving meeting transcription systems through segment-level speaker reassignment

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    Diarization is a crucial component in meeting transcription systems to ease the challenges of speech enhancement and attribute the transcriptions to the correct speaker. Particularly in the presence of overlapping or noisy speech, these systems have problems reliably assigning the correct speaker labels, leading to a significant amount of speaker confusion errors. We propose to add segment-level speaker reassignment to address this issue. By revisiting, after speech enhancement, the speaker attribution for each segment, speaker confusion errors from the initial diarization stage are significantly reduced. Through experiments across different system configurations and datasets, we further demonstrate the effectiveness and applicability in various domains. Our results show that segment-level speaker reassignment successfully rectifies at least 40% of speaker confusion word errors, highlighting its potential for enhancing diarization accuracy in meeting transcription systems.Comment: Accepted for Interspeech 202

    Prototypical Components of Honeybee Homing Flight Behavior Depend on the Visual Appearance of Objects Surrounding the Goal

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    Honeybees use visual cues to relocate profitable food sources and their hive. What bees see while navigating, depends on the appearance of the cues, the bee’s current position, orientation, and movement relative to them. Here we analyze the detailed flight behavior during the localization of a goal surrounded by cylinders that are characterized either by a high contrast in luminance and texture or by mostly motion contrast relative to the background. By relating flight behavior to the nature of the information available from these landmarks, we aim to identify behavioral strategies that facilitate the processing of visual information during goal localization. We decompose flight behavior into prototypical movements using clustering algorithms in order to reduce the behavioral complexity. The determined prototypical movements reflect the honeybee’s saccadic flight pattern that largely separates rotational from translational movements. During phases of translational movements between fast saccadic rotations, the bees can gain information about the 3D layout of their environment from the translational optic flow. The prototypical movements reveal the prominent role of sideways and up- or downward movements, which can help bees to gather information about objects, particularly in the frontal visual field. We find that the occurrence of specific prototypes depends on the bees’ distance from the landmarks and the feeder and that changing the texture of the landmarks evokes different prototypical movements. The adaptive use of different behavioral prototypes shapes the visual input and can facilitate information processing in the bees’ visual system during local navigation

    A Comparison of special education teachers’ and administrators’ perceptions of school climate factors leading to teacher attrition

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    This study examined (a) the difference between special education teachers’ and administrators’ perceptions of school climate factors that influence special education teacher attrition and (b) differences among the four school climate factors perceived by school personnel. School climate was measured in professional development, collaboration, working conditions, and leadership. Participants were 29 administrators and 62 special education teachers from a large metropolitan school district in the Southwest United States. A 52 item online questionnaire was used for data collection. Special education teachers perceived school climate factors as more influential in promoting teacher attrition than did administrators. When the four school climate factors were compared for their mean differences, both administrators and teachers rated working conditions as the most influential factor of special education teacher attrition and professional development and leadership as the least influential. Finally, school personnel did not moderate the difference among the four climate factors. Both administrators and special education teachers reported school climate factors along a similar trend. i

    The Behavioral Relevance of Landmark Texture for Honeybee Homing

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    Honeybees visually pinpoint the location of a food source using landmarks. Studies on the role of visual memories have suggested that bees approach the goal by finding a close match between their current view and a memorized view of the goal location. The most relevant landmark features for this matching process seem to be their retinal positions, the size as defined by their edges, and their color. Recently, we showed that honeybees can use landmarks that are statically camouflaged, suggesting that motion cues are relevant as well. Currently it is unclear how bees weight these different landmark features when accomplishing navigational tasks, and whether this depends on their saliency. Since natural objects are often distinguished by their texture, we investigate the behavioral relevance and the interplay of the spatial configuration and the texture of landmarks. We show that landmark texture is a feature that bees memorize, and being given the opportunity to identify landmarks by their texture improves the bees’ navigational performance. Landmark texture is weighted more strongly than landmark configuration when it provides the bees with positional information and when the texture is salient. In the vicinity of the landmark honeybees changed their flight behavior according to its texture
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