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

A computational model of primitive auditory scene analysis is described, in which the grouping of peripheral frequency channels is signalled by the pattern of temporal synchronisation in a network of neural oscillators. It is demonstrated that the model is able to group acoustic components according to their fundamental frequencies and onset times. Implications for models of pitch perception are discussed.

/pdf/a-neural-oscillator-model-of-primitive-auditory-grouping-3q9djahn5a.pdf

A neural oscillator model of primitive auditory grouping

A nonlinear auditory model is appraised in terms of its ability to encode speech formant frequencies in the fine time structure of its output. It is demonstrated that groups of model auditory nerve (AN) fibres with similar interpeak intervals accurately encode the resonances of synthetic three-formant syllables, in close agreement with physiological data. Acoustic features are derived from the interpeak intervals and used as the input to a hidden Markov model-based automatic speech recognition system. In a digits-in-noise recognition task, interval-based features gave a better performance than features based on AN firing rate at every signal-to-noise ratio tested. Index Terms: auditory model, time interval, automatic speech recognition

/pdf/the-representation-of-speech-in-a-nonlinear-auditory-model-2c3mw673d6.pdf

The representation of speech in a nonlinear auditory model: time-domain analysis of simulated auditory-nerve firing patterns

Physiologically-motivated signal representations for computational auditory scene analysis

Previously, we have proposed a reverberation‐robust system for automatic speech recognition (ASR) based on a temporal masking principle. In the first pathway of this system, speech is analysed by a bank of auditory filters, in order to provide acoustic features for the recogniser. In the second pathway, a bandpass modulation filter (1.5 Hz ‐ 8.2 Hz) detects regions of the envelope in each filter channel that contain strong speech energy. Regions of the modulation filter output that exceed a threshold are labelled as reliable evidence for the speech in a time‐frequency mask; regions that fall below the threshold are dominated by reverberation and labelled as unreliable. The acoustic features and time‐frequency mask are then decoded by a “missing data” ASR system. Here we describe modifications of this system that bring it into closer agreement with purported mechanisms of human perceptual compensation for reverberation, as determined by psychophysical studies [Watkins & Makin, JASA 121, 257‐266]. Specifica...

A reverberation‐robust automatic speech recognition system based on temporal masking

A neural model is described which uses oscillatory correlation to segregate speech from interfering sound sources. The core of the model is a two-layer neural oscillator network. The first layer of the network identifies the connected regions of energy in the time-frequency plane (segments). In the second layer, segments that have a common fundamental frequency are grouped into streams. A stream is represented by a synchronized population of relaxation oscillators, and different streams are represented by desynchronized oscillator populations. The model has been evaluated using a corpus of voiced speech mixed with interfering sounds, and produces an improvement in signal-to-noise ratio for every mixture.

/pdf/the-separation-of-speech-from-interfering-sounds-an-3u6cje7jzq.pdf

Guy J. Brown

Papers

A neural oscillator model of primitive auditory grouping

The representation of speech in a nonlinear auditory model: time-domain analysis of simulated auditory-nerve firing patterns

Physiologically-motivated signal representations for computational auditory scene analysis

A reverberation‐robust automatic speech recognition system based on temporal masking

The separation of speech from interfering sounds: an oscillatory correlation approach