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F H Guenther

Publications and source records attributed to F H Guenther.

10 recordsLinked to original sources
PubMed2001

A modeling study of potential sources of curvature in human reaching movements.

The authors of this article suggest that the slight but consistent posture-dependent curvature of the spatial paths in the kinematic transformation between intrinsic and extrinsic coordinates may result in a systematic curvature of movements initially planned as straight-line trajectories toward the target. A kinematic planning model is presented that takes into account the anisotropy of the intrinsic and extrinsic transformation and tends to avoid movements that require excessive joint rotations by introducing slight deviations from a straight-line trajectory. Preliminary simulations showed reasonably good agreement with experimental data, especially considering that the current model is strictly based on kinematics. A quantitative analysis showed that the strategy used in the model achieves a favorable compromise between straight-line movements and angular joint changes: By slightly increasing the spatial length of the movement (i.e., by introducing curvature), an individual can greatly reduce the total amount of joint rotation required to produce the movement.

Biomechanical Phenomena↗
PubMed2000

An auditory-feedback-based neural network model of speech production that is robust to developmental changes in the size and shape of the articulatory system.

The purpose of this article is to demonstrate that self-produced auditory feedback is sufficient to train a mapping between auditory target space and articulator space under conditions in which the structures of speech production are undergoing considerable developmental restructuring. One challenge for competing theories that propose invariant constriction targets is that it is unclear what teaching signal could specify constriction location and degree so that a mapping between constriction target space and articulator space can be learned. It is predicted that a model trained by auditory feedback will accomplish speech goals, in auditory target space, by continuously learning to use different articulator configurations to adapt to the changing acoustic properties of the vocal tract during development. The Maeda articulatory synthesis part of the DIVA neural network model (Guenther et al., 1998) was modified to reflect the development of the vocal tract by using measurements taken from MR images of children. After training, the model was able to maintain the 11 English vowel targets in auditory planning space, utilizing varying articulator configurations, despite morphological changes that occur during development. The vocal-tract constriction pattern (derived from the vocal-tract area function) as well as the formant values varied during the course of development in correspondence with morphological changes in the structures involved with speech production. Despite changes in the acoustical properties of the vocal tract that occur during the course of development, the model was able to demonstrate motor-equivalent speech production under lip-restriction conditions. The model accomplished this in a self-organizing manner even though there was no prior experience with lip restriction during training.

Child Development↗
PubMed1999

Articulatory tradeoffs reduce acoustic variability during American English /r/ production.

The American English phoneme /r/ has long been associated with large amounts of articulatory variability during production. This paper investigates the hypothesis that the articulatory variations used by a speaker to produce /r/ in different contexts exhibit systematic tradeoffs, or articulatory trading relations, that act to maintain a relatively stable acoustic signal despite the large variations in vocal tract shape. Acoustic and articulatory recordings were collected from seven speakers producing /r/ in five phonetic contexts. For every speaker, the different articulator configurations used to produce /r/ in the different phonetic contexts showed systematic tradeoffs, as evidenced by significant correlations between the positions of transducers mounted on the tongue. Analysis of acoustic and articulatory variabilities revealed that these tradeoffs act to reduce acoustic variability, thus allowing relatively large contextual variations in vocal tract shape for /r/ without seriously degrading the primary acoustic cue. Furthermore, some subjects appeared to use completely different articulatory gestures to produce /r/ in different phonetic contexts. When viewed in light of current models of speech movement control, these results appear to favor models that utilize an acoustic or auditory target for each phoneme over models that utilize a vocal tract shape target for each phoneme.

Female↗
PubMed1999

Effects of categorization and discrimination training on auditory perceptual space.

Psychophysical phenomena such as categorical perception and the perceptual magnet effect indicate that our auditory perceptual spaces are warped for some stimuli. This paper investigates the effects of two different kinds of training on auditory perceptual space. It is first shown that categorization training using nonspeech stimuli, in which subjects learn to identify stimuli within a particular frequency range as members of the same category, can lead to a decrease in sensitivity to stimuli in that category. This phenomenon is an example of acquired similarity and apparently has not been previously demonstrated for a category-relevant dimension. Discrimination training with the same set of stimuli was shown to have the opposite effect: subjects became more sensitive to differences in the stimuli presented during training. Further experiments investigated some of the conditions that are necessary to generate the acquired similarity found in the first experiment. The results of these experiments are used to evaluate two neural network models of the perceptual magnet effect. These models, in combination with our experimental results, are used to generate an experimentally testable prediction concerning changes in the brain's auditory maps under different training conditions.

Adolescent↗
PubMed1998

A self-organizing neural network architecture for navigation using optic flow.

This article describes a self-organizing neural network architecture that transforms optic flow and eye position information into representations of heading, scene depth, and moving object locations. These representations are used to navigate reactively in simulations involving obstacle avoidance and pursuit of a moving target. The network's weights are trained during an action-perception cycle in which self-generated eye and body movements produce optic flow information, thus allowing the network to tune itself without requiring explicit knowledge of sensor geometry. The confounding effect of eye movement during translation is suppressed by learning the relationship between eye movement outflow commands and the optic flow signals that they induce. The remaining optic flow field is due to only observer translation and independent motion of objects in the scene. A self-organizing feature map categorizes normalized translational flow patterns, thereby creating a map of cells that code heading directions. Heading information is then recombined with translational flow patterns in two different ways to form maps of scene depth and moving object locations. Most of the learning processes take place concurrently and evolve through unsupervised learning. Mapping the learned heading representations onto heading labels or motor commands requires additional structure. Simulations of the network verify its performance using both noise-free and noisy optic flow information.

Computer Simulation↗
PubMed1998

A theoretical investigation of reference frames for the planning of speech movements.

Does the speech motor control system use invariant vocal tract shape targets when producing vowels and semivowels? A 4-part theoretical treatment favoring models whose only invariant targets are regions in auditory perceptual space over models that posit invariant constriction targets is presented. Auditory target regions are hypothesized to arise during development as an emergent property of neural map formation in the auditory system. Furthermore, speech movements are planned as trajectories in auditory perceptual space. These trajectories are then mapped into articulator movements through a neural mapping that allows motor equivalent variability in constriction locations and degrees when needed. These hypotheses are illustrated using computer simulations of the DIVA model of speech acquisition and production. Finally, several difficult challenges to proponents of constriction theories based on this theoretical treatment are posed.

Humans↗
PubMed1996

The perceptual magnet effect as an emergent property of neural map formation.

The perceptual magnet effect is one of the earliest known language-specific phenomena arising in infant speech development. The effect is characterized by a warping of perceptual space near phonemic category centers. Previous explanations have been formulated within the theoretical framework of cognitive psychology. The model proposed in this paper builds on research from both psychology and neuroscience in working toward a more complete account of the effect. The model embodies two principal hypotheses supported by considerable experimental and theoretical research from the neuroscience literature: (1) sensory experience guides language-specific development of an auditory neural map, and (2) a population vector can predict psychological phenomena based on map cell activities. These hypotheses are realized in a self-organizing neural network model. The magnet effect arises in the model from language-specific nonuniformities in the distribution of map cell firing preferences. Numerical simulations verify that the model captures the known general characteristics of the magnet effect and provides accurate fits to specific psychophysical data.

Auditory Perception↗
PubMed1995

Speech sound acquisition, coarticulation, and rate effects in a neural network model of speech production.

This article describes a neural network model of speech motor skill acquisition and speech production that explains a wide range of data on variability, motor equivalence, coarticulation, and rate effects. Model parameters are learned during a babbling phase. To explain how infants learn language-specific variability limits, speech sound targets take the form of convex regions, rather than points, in orosensory coordinates. Reducing target size for better accuracy during slower speech leads to differential effects for vowels and consonants, as seen in experiments previously used as evidence for separate control processes for the 2 sound types. Anticipatory coarticulation arises when targets are reduced in size on the basis of context; this generalizes the well-known look-ahead model of coarticulation. Computer simulations verify the model's properties.

Humans↗
PubMed1994

A neural network model of speech acquisition and motor equivalent speech production.

This article describes a neural network model that addresses the acquisition of speaking skills by infants and subsequent motor equivalent production of speech sounds. The model learns two mappings during a babbling phase. A phonetic-to-orosensory mapping specifies a vocal tract target for each speech sound; these targets take the form of convex regions in orosensory coordinates defining the shape of the vocal tract. The babbling process wherein these convex region targets are formed explains how an infant can learn phoneme-specific and language-specific limits on acceptable variability of articulator movements. The model also learns an orosensory-to-articulatory mapping wherein cells coding desired movement directions in orosensory space learn articulator movements that achieve these orosensory movement directions. The resulting mapping provides a natural explanation for the formation of coordinative structures. This mapping also makes efficient use of redundancy in the articulator system, thereby providing the model with motor equivalent capabilities. Simulations verify the model's ability to compensate for constraints or perturbations applied to the articulators automatically and without new learning and to explain contextual variability seen in human speech production.

Child↗