HCU400: An Annotated Dataset for Exploring Aural Phenomenology Through Causal Uncertainty

The way we perceive a sound depends on many aspects-- its ecological frequency, acoustic features, typicality, and most notably, its identified source. In this paper, we present the HCU400: a dataset of 402 sounds ranging from easily identifiable everyday sounds to intentionally obscured artificial ones. It aims to lower the barrier for the study of aural phenomenology as the largest available audio dataset to include an analysis of causal attribution. Each sample has been annotated with crowd-sourced descriptions, as well as familiarity, imageability, arousal, and valence ratings. We extend existing calculations of causal uncertainty, automating and generalizing them with word embeddings. Upon analysis we find that individuals will provide less polarized emotion ratings as a sound's source becomes increasingly ambiguous; individual ratings of familiarity and imageability, on the other hand, diverge as uncertainty increases despite a clear negative trend on average

Investigating Perceptual Congruence Between Data and Display Dimensions in Sonification

The relationships between sounds and their perceived meaning and connotations are complex, making auditory perception an important factor to consider when designing sonification systems. Listeners often have a mental model of how a data variable should sound during sonification and this model is not considered in most data:sound mappings. This can lead to mappings that are difficult to use and can cause confusion. To investigate this issue, we conducted a magnitude estimation experiment to map how roughness, noise and pitch relate to the perceived magnitude of stress, error and danger. These parameters were chosen due to previous findings which suggest perceptual congruency between these auditory sensations and conceptual variables. Results from this experiment show that polarity and scaling preference are dependent on the data:sound mapping. This work provides polarity and scaling values that may be directly utilised by sonification designers to improve auditory displays in areas such as accessible and mobile computing, process-monitoring and biofeedback

The effects of attention sharing in a dynamic dual task environment

There are numerous examples of cases where the human operator is confronted with several tasks occurring simultaneously and continuously in time. The current study is an investigation into the nature of attention sharing between two continuous tasks with independent input-output modes. Eleven subjects were tested using a zero order compensatory control task with three levels of difficulty (input bandwidth) for each subject. As a secondary task on half of the trials, the subjects were also required to verbally shadow a random auditory input. Results from an extensive time and frequency domain analysis of the data are presented and discussed. The evidence supports a single channel model for continuous dual-task control

The plasticity of the human perceptual systems in processing auditory- and spatial-frequencies

A common technique in research on visual and auditory perception is to embed stimuli in noise. The traditional assumption is that, when noisy stimuli are repeatedly presented to an observer, each noise component remains equally unpredictable. I challenged that assumption by running two experiments - with visual and auditory stimuli, respectively - under different noise conditions, some of which give the visual (auditory) system the opportunity to learn characteristics of the noise - a form of perceptual learning. The visual stimuli that I used were Gabor patches - spatial patterns that varied sinusoidally in luminance across the image. The visual system is thought to processes spatial patterns through a series of independent channels, each functioning as a band-pass filter centred around a specific spatial-frequency and thus tuned to a sinusoidal pattern of that frequency. The main property to be determined for each selective channel is its width on the spatial-frequency axis. This has been done by using noise masking, i.e. embedding the sinusoid in notched noise - noise from which certain frequency components have been removed - and gradually increasing the width of the notch until no further improvement in threshold is obtained. The auditory stimuli were defined in analogy with the visual ones. My prediction was that the estimates of channel widths derived via noise masking will depend on the way in which the noisy stimuli are presented. My results confirmed that perceptual learning does occur in vision, and to a lesser degree in hearing, thus suggesting that the auditory channels are more "rigid" than those in vision. The sense in which the visual system is deemed to be more "plastic" is discussed in detail. I conclude that context can influence data obtained in notched-noise masking paradigms, and I discuss the possible implications that this might have in other psychophysical investigations

Characterizing the perceptual diffusion of auditory lateralization images

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (leaf 44).When two statistically independent noise sources with different interaural time delays are presented simultaneously over headphones, the separated source images seem to become diffuse and merge over time. Experiments were designed to test the hypothesis that the measure of diffusion perceived would increase over time. Target stimuli were created consisting of the two simultaneous sources with different interaural time delays, and attempts were made to study the diffusion as a function of stimulus duration, as well as relative onset of the two noise sources. These target stimuli were compared to a set of partially decorrelated noise stimuli composed of three statistically independent sources. It was hoped that by varying the degree of decorrelation in these comparison stimuli, one could simulate different stages in the transition from two source images to one merged image observed in the target stimuli. The experiments failed to produce the expected results, but strategies for improved experimental designs were devised.by Neelima Yeddanapudi.M.Eng

The functional organization of the left STS: a large scale meta-analysis of PET and fMRI studies of healthy adults

The superior temporal sulcus (STS) in the left hemisphere is functionally diverse, with sub-areas implicated in both linguistic and non-linguistic functions. However, the number and boundaries of distinct functional regions remain to be determined. Here, we present new evidence, from meta-analysis of a large number of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies, of different functional specificity in the left STS supporting a division of its middle to terminal extent into at least three functional areas. The middle portion of the left STS stem (fmSTS) is highly specialized for speech perception and the processing of language material. The posterior portion of the left STS stem (fpSTS) is highly versatile and involved in multiple functions supporting semantic memory and associative thinking. The fpSTS responds to both language and non-language stimuli but the sensitivity to non-language material is greater. The horizontal portion of the left STS stem and terminal ascending branches (ftSTS) display intermediate functional specificity, with the anterior ascending branch adjoining the supramarginal gyrus (fatSTS) supporting executive functions and motor planning and showing greater sensitivity to language material, and the horizontal stem and posterior ascending branch adjoining the angular gyrus (fptSTS) supporting primarily semantic processing and displaying greater sensitivity to non-language material. We suggest that the high functional specificity of the left fmSTS for speech is an important means by which the human brain achieves exquisite affinity and efficiency for native speech perception. In contrast, the extreme multi-functionality of the left fpSTS reflects the role of this area as a cortical hub for semantic processing and the extraction of meaning from multiple sources of information. Finally, in the left ftSTS, further functional differentiation between the dorsal and ventral aspect is warranted

Network constraints on learnability of probabilistic motor sequences

Human learners are adept at grasping the complex relationships underlying incoming sequential input. In the present work, we formalize complex relationships as graph structures derived from temporal associations in motor sequences. Next, we explore the extent to which learners are sensitive to key variations in the topological properties inherent to those graph structures. Participants performed a probabilistic motor sequence task in which the order of button presses was determined by the traversal of graphs with modular, lattice-like, or random organization. Graph nodes each represented a unique button press and edges represented a transition between button presses. Results indicate that learning, indexed here by participants' response times, was strongly mediated by the graph's meso-scale organization, with modular graphs being associated with shorter response times than random and lattice graphs. Moreover, variations in a node's number of connections (degree) and a node's role in mediating long-distance communication (betweenness centrality) impacted graph learning, even after accounting for level of practice on that node. These results demonstrate that the graph architecture underlying temporal sequences of stimuli fundamentally constrains learning, and moreover that tools from network science provide a valuable framework for assessing how learners encode complex, temporally structured information.Comment: 29 pages, 4 figure

Autonomous Collision avoidance for Unmanned aerial systems

Unmanned Aerial System (UAS) applications are growing day by day and this will lead Unmanned Aerial Vehicle (UAV) in the close future to share the same airspace of manned aircraft.This implies the need for UAS to define precise safety standards compatible with operations standards for manned aviation. Among these standards the need for a Sense And Avoid (S&A) system to support and, when necessary, sub¬stitute the pilot in the detection and avoidance of hazardous situations (e.g. midair collision, controlled flight into terrain, flight path obstacles, and clouds). This thesis presents the work come out in the development of a S&A system taking into account collision risks scenarios with multiple moving and fixed threats. The conflict prediction is based on a straight projection of the threats state in the future. The approximations introduced by this approach have the advantage of high update frequency (1 Hz) of the estimated conflict geometry. This solution allows the algorithm to capture the trajectory changes of the threat or ownship. The resolution manoeuvre evaluation is based on a optimisation approach considering step command applied to the heading and altitude autopilots. The optimisation problem takes into account the UAV performances and aims to keep a predefined minimum separation distance between UAV and threats during the resolution manouvre. The Human-Machine Interface (HMI) of this algorithm is then embedded in a partial Ground Control Station (GCS) mock-up with some original concepts for the indication of the flight condition parameters and the indication of the resolution manoeuvre constraints. Simulations of the S&A algorithm in different critical scenarios are moreover in-cluded to show the algorithm capabilities. Finally, methodology and results of the tests and interviews with pilots regarding the proposed GCS partial layout are covered

Using Sound to Represent Uncertainty in Spatial Data

There is a limit to the amount of spatial data that can be shown visually in an effective manner, particularly when the data sets are extensive or complex. Using sound to represent some of these data (sonification) is a way of avoiding visual overload. This thesis creates a conceptual model showing how sonification can be used to represent spatial data and evaluates a number of elements within the conceptual model. These are examined in three different case studies to assess the effectiveness of the sonifications. Current methods of using sonification to represent spatial data have been restricted by the technology available and have had very limited user testing. While existing research shows that sonification can be done, it does not show whether it is an effective and useful method of representing spatial data to the end user. A number of prototypes show how spatial data can be sonified, but only a small handful of these have performed any user testing beyond the authors’ immediate colleagues (where n > 4). This thesis creates and evaluates sonification prototypes, which represent uncertainty using three different case studies of spatial data. Each case study is evaluated by a significant user group (between 45 and 71 individuals) who completed a task based evaluation with the sonification tool, as well as reporting qualitatively their views on the effectiveness and usefulness of the sonification method. For all three case studies, using sound to reinforce information shown visually results in more effective performance from the majority of the participants than traditional visual methods. Participants who were familiar with the dataset were much more effective at using the sonification than those who were not and an interactive sonification which requires significant involvement from the user was much more effective than a static sonification, which did not provide significant user engagement. Using sounds with a clear and easily understood scale (such as piano notes) was important to achieve an effective sonification. These findings are used to improve the conceptual model developed earlier in this thesis and highlight areas for future research