Detection of appearing and disappearing objects in complex acoustic scenes.

The ability to detect sudden changes in the environment is critical for survival. Hearing is hypothesized to play a major role in this process by serving as an "early warning device," rapidly directing attention to new events. Here, we investigate listeners' sensitivity to changes in complex acoustic scenes-what makes certain events "pop-out" and grab attention while others remain unnoticed? We use artificial "scenes" populated by multiple pure-tone components, each with a unique frequency and amplitude modulation rate. Importantly, these scenes lack semantic attributes, which may have confounded previous studies, thus allowing us to probe low-level processes involved in auditory change perception. Our results reveal a striking difference between "appear" and "disappear" events. Listeners are remarkably tuned to object appearance: change detection and identification performance are at ceiling; response times are short, with little effect of scene-size, suggesting a pop-out process. In contrast, listeners have difficulty detecting disappearing objects, even in small scenes: performance rapidly deteriorates with growing scene-size; response times are slow, and even when change is detected, the changed component is rarely successfully identified. We also measured change detection performance when a noise or silent gap was inserted at the time of change or when the scene was interrupted by a distractor that occurred at the time of change but did not mask any scene elements. Gaps adversely affected the processing of item appearance but not disappearance. However, distractors reduced both appearance and disappearance detection. Together, our results suggest a role for neural adaptation and sensitivity to transients in the process of auditory change detection, similar to what has been demonstrated for visual change detection. Importantly, listeners consistently performed better for item addition (relative to deletion) across all scene interruptions used, suggesting a robust perceptual representation of item appearance

Sensory Communication

Contains table of contents for Section 2 and reports on five research projects.National Institutes of Health Contract 2 R01 DC00117National Institutes of Health Contract 1 R01 DC02032National Institutes of Health Contract 2 P01 DC00361National Institutes of Health Contract N01 DC22402National Institutes of Health Grant R01-DC001001National Institutes of Health Grant R01-DC00270National Institutes of Health Grant 5 R01 DC00126National Institutes of Health Grant R29-DC00625U.S. Navy - Office of Naval Research Grant N00014-88-K-0604U.S. Navy - Office of Naval Research Grant N00014-91-J-1454U.S. Navy - Office of Naval Research Grant N00014-92-J-1814U.S. Navy - Naval Air Warfare Center Training Systems Division Contract N61339-94-C-0087U.S. Navy - Naval Air Warfare Center Training System Division Contract N61339-93-C-0055U.S. Navy - Office of Naval Research Grant N00014-93-1-1198National Aeronautics and Space Administration/Ames Research Center Grant NCC 2-77

Do audio-visual motion cues promote segregation of auditory streams?

An audio-visual experiment using moving sound sources was designed to investigate whether the analysis of auditory scenes is modulated by synchronous presentation of visual information. Listeners were presented with an alternating sequence of two pure tones delivered by two separate sound sources. In different conditions, the two sound sources were either stationary or moving on random trajectories around the listener. Both the sounds and the movement trajectories were derived from recordings in which two humans were moving with loudspeakers attached to their heads. Visualized movement trajectories modeled by a computer animation were presented together with the sounds. In the main experiment, behavioral reports on sound organization were collected from young healthy volunteers. The proportion and stability of the different sound organizations were compared between the conditions in which the visualized trajectories matched the movement of the sound sources and when the two were independent of each other. The results corroborate earlier findings that separation of sound sources in space promotes segregation. However, no additional effect of auditory movement per se on the perceptual organization of sounds was obtained. Surprisingly, the presentation of movement-congruent visual cues did not strengthen the effects of spatial separation on segregating auditory streams. Our findings are consistent with the view that bistability in the auditory modality can occur independently from other modalities

Continuous Analysis of Affect from Voice and Face

Human affective behavior is multimodal, continuous and complex. Despite major advances within the affective computing research field, modeling, analyzing, interpreting and responding to human affective behavior still remains a challenge for automated systems as affect and emotions are complex constructs, with fuzzy boundaries and with substantial individual differences in expression and experience [7]. Therefore, affective and behavioral computing researchers have recently invested increased effort in exploring how to best model, analyze and interpret the subtlety, complexity and continuity (represented along a continuum e.g., from −1 to +1) of affective behavior in terms of latent dimensions (e.g., arousal, power and valence) and appraisals, rather than in terms of a small number of discrete emotion categories (e.g., happiness and sadness). This chapter aims to (i) give a brief overview of the existing efforts and the major accomplishments in modeling and analysis of emotional expressions in dimensional and continuous space while focusing on open issues and new challenges in the field, and (ii) introduce a representative approach for multimodal continuous analysis of affect from voice and face, and provide experimental results using the audiovisual Sensitive Artificial Listener (SAL) Database of natural interactions. The chapter concludes by posing a number of questions that highlight the significant issues in the field, and by extracting potential answers to these questions from the relevant literature. The chapter is organized as follows. Section 10.2 describes theories of emotion, Sect. 10.3 provides details on the affect dimensions employed in the literature as well as how emotions are perceived from visual, audio and physiological modalities. Section 10.4 summarizes how current technology has been developed, in terms of data acquisition and annotation, and automatic analysis of affect in continuous space by bringing forth a number of issues that need to be taken into account when applying a dimensional approach to emotion recognition, namely, determining the duration of emotions for automatic analysis, modeling the intensity of emotions, determining the baseline, dealing with high inter-subject expression variation, defining optimal strategies for fusion of multiple cues and modalities, and identifying appropriate machine learning techniques and evaluation measures. Section 10.5 presents our representative system that fuses vocal and facial expression cues for dimensional and continuous prediction of emotions in valence and arousal space by employing the bidirectional Long Short-Term Memory neural networks (BLSTM-NN), and introduces an output-associative fusion framework that incorporates correlations between the emotion dimensions to further improve continuous affect prediction. Section 10.6 concludes the chapter

Multi-Level Audio-Visual Interactions in Speech and Language Perception

That we perceive our environment as a unified scene rather than individual streams of auditory, visual, and other sensory information has recently provided motivation to move past the long-held tradition of studying these systems separately. Although they are each unique in their transduction organs, neural pathways, and cortical primary areas, the senses are ultimately merged in a meaningful way which allows us to navigate the multisensory world. Investigating how the senses are merged has become an increasingly wide field of research in recent decades, with the introduction and increased availability of neuroimaging techniques. Areas of study range from multisensory object perception to cross-modal attention, multisensory interactions, and integration. This thesis focuses on audio-visual speech perception, with special focus on facilitatory effects of visual information on auditory processing. When visual information is concordant with auditory information, it provides an advantage that is measurable in behavioral response times and evoked auditory fields (Chapter 3) and in increased entrainment to multisensory periodic stimuli reflected by steady-state responses (Chapter 4). When the audio-visual information is incongruent, the combination can often, but not always, combine to form a third, non-physically present percept (known as the McGurk effect). This effect is investigated (Chapter 5) using real word stimuli. McGurk percepts were not robustly elicited for a majority of stimulus types, but patterns of responses suggest that the physical and lexical properties of the auditory and visual stimulus may affect the likelihood of obtaining the illusion. Together, these experiments add to the growing body of knowledge that suggests that audio-visual interactions occur at multiple stages of processing

Automatic Measurement of Affect in Dimensional and Continuous Spaces: Why, What, and How?

This paper aims to give a brief overview of the current state-of-the-art in automatic measurement of affect signals in dimensional and continuous spaces (a continuous scale from -1 to +1) by seeking answers to the following questions: i) why has the field shifted towards dimensional and continuous interpretations of affective displays recorded in real-world settings? ii) what are the affect dimensions used, and the affect signals measured? and iii) how has the current automatic measurement technology been developed, and how can we advance the field

A Visionary Approach to Listening: Determining The Role Of Vision In Auditory Scene Analysis

To recognize and understand the auditory environment, the listener must first separate sounds that arise from different sources and capture each event. This process is known as auditory scene analysis. The aim of this thesis is to investigate whether and how visual information can influence auditory scene analysis. The thesis consists of four chapters. Firstly, I reviewed the literature to give a clear framework about the impact of visual information on the analysis of complex acoustic environments. In chapter II, I examined psychophysically whether temporal coherence between auditory and visual stimuli was sufficient to promote auditory stream segregation in a mixture. I have found that listeners were better able to report brief deviants in an amplitude modulated target stream when a visual stimulus changed in size in a temporally coherent manner than when the visual stream was coherent with the non-target auditory stream. This work demonstrates that temporal coherence between auditory and visual features can influence the way people analyse an auditory scene. In chapter III, the integration of auditory and visual features in auditory cortex was examined by recording neuronal responses in awake and anaesthetised ferret auditory cortex in response to the modified stimuli used in Chapter II. I demonstrated that temporal coherence between auditory and visual stimuli enhances the neural representation of a sound and influences which sound a neuron represents in a sound mixture. Visual stimuli elicited reliable changes in the phase of the local field potential which provides mechanistic insight into this finding. Together these findings provide evidence that early cross modal integration underlies the behavioural effects in chapter II. Finally, in chapter IV, I investigated whether training can influence the ability of listeners to utilize visual cues for auditory stream analysis and showed that this ability improved by training listeners to detect auditory-visual temporal coherence

Sensory Communication

Contains table of contents for Section 2, an introduction and reports on twelve research projects.National Institutes of Health Grant 5 R01 DC00117National Institutes of Health Contract 2 P01 DC00361National Institutes of Health Grant 5 R01 DC00126National Institutes of Health Grant R01-DC00270U.S. Air Force - Office of Scientific Research Contract AFOSR-90-0200National Institutes of Health Grant R29-DC00625U.S. Navy - Office of Naval Research Grant N00014-88-K-0604U.S. Navy - Office of Naval Research Grant N00014-91-J-1454U.S. Navy - Office of Naval Research Grant N00014-92-J-1814U.S. Navy - Naval Training Systems Center Contract N61339-93-M-1213U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0055U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0083U.S. Navy - Office of Naval Research Grant N00014-92-J-4005U.S. Navy - Office of Naval Research Grant N00014-93-1-119

An Object-Based Interpretation of Audiovisual Processing

Visual cues help listeners follow conversation in a complex acoustic environment. Many audiovisual research studies focus on how sensory cues are combined to optimize perception, either in terms of minimizing the uncertainty in the sensory estimate or maximizing intelligibility, particularly in speech understanding. From an auditory perception perspective, a fundamental question that has not been fully addressed is how visual information aids the ability to select and focus on one auditory object in the presence of competing sounds in a busy auditory scene. In this chapter, audiovisual integration is presented from an object-based attention viewpoint. In particular, it is argued that a stricter delineation of the concepts of multisensory integration versus binding would facilitate a deeper understanding of the nature of how information is combined across senses. Furthermore, using an object-based theoretical framework to distinguish binding as a distinct form of multisensory integration generates testable hypotheses with behavioral predictions that can account for different aspects of multisensory interactions. In this chapter, classic multisensory illusion paradigms are revisited and discussed in the context of multisensory binding. The chapter also describes multisensory experiments that focus on addressing how visual stimuli help listeners parse complex auditory scenes. Finally, it concludes with a discussion of the potential mechanisms by which audiovisual processing might resolve competition between concurrent sounds in order to solve the cocktail party problem