There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

자연주의적 탐구조사(Naturalistic Inquiry)

Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The outside world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the governing laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Several lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual \"filling in,\" visual stability despite eye movements, change blindness, sensory substitution, and color perception.

A sensorimotor account of vision and visual consciousness-Authors' Response-Acting out our sensory experience

Auditory scene analysis (ASA) is defined and the problem of partitioning the time-varying spectrum resulting from mixtures of individual acoustic signals is described Some basic facts about ASA are presented These include causes and effects of auditory organization (sequential, simultaneous, and the old-plus-new heuristic) Processes employing different cues collaborate and compete in determining the final organization of the mixture These processes take advantage of regularities in the mixture that give clues about how to parse it There are general regularities that apply to most types of sound, as well as regularities in particular types of sound The general ones are hypothesized to be used by innate processes, and the ones specific to restricted environments to be used by learned processes in humans and possibly by innate ones in animals The use of brain recordings and the study of nonhuman animals is discussed

Auditory Scene Analysis

The computational brain: Patricia S. Churchland and Terrence J. Sejnowski (MIT Press, Cambridge, MA, 1992); xi, 544 pages, $39.95

Sleep-disordered breathing (SDB) is a serious and prevalent condition, and acoustic analysis via consumer devices (e.g. smartphones) offers a low-cost solution to screening for it. We present a novel approach for the acoustic identification of SDB sounds, such as snoring, using bottleneck features learned from a corpus of whole-night sound recordings. Two types of bottleneck features are described, obtained by applying a deep autoencoder to the output of an auditory model or a short-term autocorrelation analysis. We investigate two architectures for snore sound detection: a tandem system and a hybrid system. In both cases, a ‘language model’ (LM) was incorporated to exploit information about the sequence of different SDB events. Our results show that the proposed bottleneck features give better performance than conventional mel-frequency cepstral coefficients, and that the tandem system outperforms the hybrid system given the limited amount of labelled training data available. The LM made a small improvement to the performance of both classifiers.

/pdf/deep-learning-features-for-robust-detection-of-acoustic-33ihcws5t5.pdf

Deep Learning Features for Robust Detection of Acoustic Events in Sleep-disordered Breathing

Overlapping talk is common in talk-in-interaction. Much of the previous research on this topic agrees that speaker overlaps can be either turn competitive or noncompetitive. An investigation of the differences in prosodic design between these two classes of overlaps can offer insight into how speakers use and orient to prosody as a resource for turn competition.
In this paper, we investigate the role of fundamental frequency (F0) as a resource for turn competition in overlapping speech. Our methodological approach combines detailed conversation analysis of overlap instances with acoustic measurements of F0 in the overlapping sequence and in its local context. The analyses are based on a collection of overlap instances drawn from the ICSI Meeting corpus. We found that overlappers mark an overlapping incoming as competitive by raising F0 above their norm for turn beginnings, and retaining this higher F0 until the point of overlap resolution. Overlappees may respond to these competitive incomings by returning competition, in which case they raise their F0 too. Our results thus provide instrumental support for earlier claims made on impressionistic evidence, namely that participants in talk-in-interaction systematically manipulate F0 height when competing for the turn.

/pdf/fundamental-frequency-height-as-a-resource-for-the-497a9ty81c.pdf

Fundamental Frequency Height as a Resource for the Management of Overlap in Talk-in-Interaction

Mask estimation and imputation methods for missing data speech recognition in a multisource reverberant environment

Speech localisation in multitalker mixtures is affected by the listener’s expectations about the spatial arrangement of the sound sources. This effect was investigated via experiments with human listeners and a machine system, in which the task was to localise a female-voice target among four spatially distributed male-voice maskers. Two configurations were used: either the masker locations were fixed or the locations varied from trial-to-trial. The machine system uses deep neural networks (DNNs) to learn the relationship between binaural cues and source azimuth, and exploits top-down knowledge about the spectral characteristics of the target source. Performance was examined in both anechoic and reverberant conditions. Our experiments show that the machine system outperformed listeners in some conditions. Both the machine and listeners were able to make use of a priori knowledge about the spatial configuration of the sources, but the effect for headphone listening was smaller than that previously reported for listening in a real room.

/pdf/speech-localisation-in-a-multitalker-mixture-by-humans-and-4opnq6jodq.pdf

Speech localisation in a multitalker mixture by humans and machines

How are acoustic features that are extracted in remote regions of the auditory system bound together to form a perceptual whole? We consider the evidence for a solution to this so-called binding problem, which proposes that the responses of feature detecting cells are bound together by the synchronisation of oscillatory firing activity. Four models of auditory grouping based on neural oscillators are reviewed, and issues arising from these models are discussed.

/pdf/are-neural-oscillations-the-substrate-of-auditory-grouping-25rcufokti.pdf

Guy J. Brown

Papers

Deep Learning Features for Robust Detection of Acoustic Events in Sleep-disordered Breathing

Fundamental Frequency Height as a Resource for the Management of Overlap in Talk-in-Interaction

Mask estimation and imputation methods for missing data speech recognition in a multisource reverberant environment

Speech localisation in a multitalker mixture by humans and machines

Are neural oscillations the substrate of auditory grouping