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A new perspective on phonetic variation is achieved in this volume through the construction of a series of models of spoken American English. In the past, computer theorists and programmers investigating pronunciation have often relied on their own knowledge of the language or on limited transcription data. Speech recognition researchers, on the other hand, have drawn on a great deal of data but without examining in detail the information about pronunciation the data contains. The authors combine the best of each approach to develop probabilistic and rule-based computational models of transcription data. An ongoing controversy in studies of phonetic variation is the existence and proper definition of a phonetic unit. The authors argue that assumptions about the units of spoken language are critical to a computational model. Their computational models employ suprasegmental elements such as syllable boundaries, stress, and position in a unit called a metrical foot. The use of such elements in modeling data enables the creation of better computational models for both recognition and synthesis technology. This book should be of interest to speech engineers, linguists, and anyone who wishes to understand symbolic systems of communication.
How do infants learn a language? Why and how do languages evolve? How do we understand a sentence? This book explores these questions using recent computational models that shed new light on issues related to language and cognition. The chapters in this collection propose original analyses of specific problems and develop computational models that have been tested and evaluated on real data. Featuring contributions from a diverse group of experts, this interdisciplinary book bridges the gap between natural language processing and cognitive sciences. It is divided into three sections, focusing respectively on models of neural and cognitive processing, data driven methods, and social issues in language evolution. This book will be useful to any researcher and advanced student interested in the analysis of the links between the brain and the language faculty.
The prosody of spontaneous speech - A typology of spontaneous speech - Prosody, models, and spontaneous speech - On the analysis of prosody in interaction - Prosody and the structure of the message - Integrating prosodic and discourse modelling - Prosodic features of utterances in task-oriented dialogues - Variation of accent prominence within the phrase : models and spontaneous speech data - Predicting the intonation of discourse segments from examples in dialogue speech - Effects of focus on duration and vowel formant frequency in Japanese - Prosody in speech synthesis - Synthesizing spontaneous speech - Modelling prosody in spontaneous speech - Comparison of FO control rules derived from multiple speech databases - Segmental duration and speech timing - Measuring temporal compensation effect in speech perception - Prediction of major phrase boundary location and pause insertion using a stochastic context-free grammar - Prosody in speech recognition - A multi-level model for recognit ...
Proceedings of the NATO Advanced Study Institute on Computational Models of Speech Pattern Processing, held in St. Helier, Jersey, UK, July 7-18, 1997
Cognitive Models of Speech Processing presents extensive reviews of current thinking on psycholinguistic and computational topics in speech recognition and natural-language processing, along with a substantial body of new experimental data and computational simulations. Topics range from lexical access and the recognition of words in continuous speech to syntactic processing and the relationship between syntactic and intonational structure. A Bradford Book. ACL-MIT Press Series in Natural Language Processing
A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.
In doing so, computational modeling provides insight into the plausible mechanisms involved in human language acquisition, and inspires the development of better language models and techniques. This book provides an overview of the main research quesetions in the field of human language acquisition. It reviews the most commonly used computational frameworks, methodologies and resources for modeling child language learning, and the evaluation techniques used for assessing these computational models. The book is aimed at cognitive scientists who want to become familiar with the available computational methods for investigating problems related to human language acquisition, as well as computational linguists who are interested in applying their skills to the study of child language acquisition.