Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves; the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands; indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context-dependent while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction.

A parallel distributed processing model of visual word recognition and pronunciation is described. The model consists of sets of orthographic and phonologlc ~ units and an interlevel of hidden units. Weights on connections between units were modified during a training phase using the back-propa-gation learning algorithm. The model simulates many aspects of human performance, including (a) differences bet~n~.'n words in terms of processing difficulty, (b) pronunciation of novel items, (c) differences between readers in terms of word recognition skill, (d) transitions from beginning to skilled reading, and (e) differences in performance on lexieal decision and naming tasks. The model's behavior early in the learning phase corresponds to that of children acquiring word recognition skills. Training with a smaller number of hidden units produces output characteristic of many dys-lexic readers. Naming is simulated without pronunciation rules, and lexical decisions are simulated without accessing word-level representations. The performance of the model is largely determined by three factors: the nature of the input, a significant fragment of written English; the learning rule, which encodes the implicit structure of the orthography in the weights on connections; and the architecture of the system, which influences the scope of what can be learned. The recognition and pronunciation of words is one of the cen-

Introduction Despite considerable diversity among theories about how humans process language, there are a number of fundamental assumptions which are shared by most such theories. This consensus extends to the very basic question about what counts as a cognitive process. So although many cognitive scientists are fond of referring to the brain as a `mental organ' (e.g., Chomsky, 1975)---implying a similarity to other organs such as the liver or kidneys---it is also assumed that the brain is an organ with special properties which set it apart. Brains `carry out computation' (it is argued)

The failure to document isochronous interstress intervals in spoken English may be attributed to the unconstrained nature of most experimental tasks. Some experiments are described which probe the degree to which the relative durations of interstress intervals within a series of repeated phrases are independent. The experiments introduce a novel paradigm, `speech cycling', for investigating temporal phenomena in speech. The data reveal the presence of strong rhythmic constraints on stress timing which have hitherto eluded experimenters. It is argued that these constraints are evidence for a task-specific dynamical system in which prominent events (stress beats) are constrained to occur at specific, predictable, phases of an enclosing cycle. The dynamical system is characterized by entrainment between metrical levels, a principle which underlies rhythmic coordination in activities such as locomotion. 1 Introduction Numerous phoneticians have suggested that English speech tends to exh...

this paper. 3. uppu: Through the hoop a poodle jumped 4. *tt*: They are going to fit a timber roof on our house. 5. aettae: We gave the cat a tag to wear round its neck. 6. uttu: The robbers went to loot a tomb. 7. *kk*: You may pick a kitten from the basket. 8. aekkae: I forgot to pack a can of coffee for him. 9. ukku: I gave Luke a cool drink. 2.2 Results

We describe a new model for the formal representation of the rhythmic tendencies of natural languages. The algorithm is a modification of PVI, proposed by Grabe and Low [10]. The model was tested on a fairly substantial corpus of Italian semispontaneous productions, and its outcome compared with that yielded by two well-known algorithms (Ramus [14] and PVI). 1.

Researchers have interpreted the behaviours of individuals with acquired apraxia of speech (AOS) as impairment of linguistic phonological processing, motor control, or both. Acoustic, kinematic, and perceptual studies of speech in more recent years have led to significant advances in our understanding of the disorder and wide acceptance that it affects phonetic-motoric planning of speech. However, newly developed methods for studying nonspeech motor control are providing new insights, indicating that the motor control impairment of AOS extends beyond speech and is manifest in nonspeech movements of the oral structures. We present the most recent developments in theory and methods to examine and define the nature of AOS. Theories of the disorder are then related to existing treatment approaches and the efficacy of these approaches is examined. Directions for development of new treatments are posited. It is proposed that treatment programmes driven by a principled account of how the motor system learns to produce skilled actions will provide the most efficient and effective framework for treating motorbased

This paper presents recent research which provides an over-arching model of exemplar theory capable of explaining phenomena across the phonetic and syntactic strata. The model represents a unique exemplar-based account of constituency interactions encompassing both linguistic domains. It yields simulation and experimental results in keeping with experimental findings in the literature on syllable duration variability and offers an exemplar-theoretic account of local grammaticality. In addition, it provides some insights into the nature of exemplar cloud formation, and demonstrates experimentally the potential gains that can be enjoyed via the use of rich exemplar representations. Exemplar Theory was initially proposed in the domain of psychology (Nosofsky, 1986; Hintzman, 1986). However, recent years have seen a growing body of research into exemplar-based

Towards a unified predictive model of Speech Rhythm