The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research.
This book describes a study on the question of what sort of innate knowledge it is that enables children to acquire a first language. The author, using a computational approach, builds a model, named BUD (Bring Up a Daughter), on the basis of the data linguists and psychologists have collected.BUD is based on the empirists, view of first language acquisition (as opposed to that of the nativists'), that children make a number of rules in acquiring a first language and that over generalizations can be found in the acquisition of every aspect of a language. Thus, BUD has no built-in procedure by which it computes the structures of a language. A detailed description of the BUD model and its workings answers the question on which the study is based.
This volume features the complete text of the material presented at the Twenty-Fourth Annual Conference of the Cognitive Science Society. As in previous years, the symposium included an interesting mixture of papers on many topics from researchers with diverse backgrounds and different goals, presenting a multifaceted view of cognitive science. The volume includes all papers, posters, and summaries of symposia presented at this leading conference that brings cognitive scientists together. The 2002 meeting dealt with issues of representing and modeling cognitive processes as they appeal to scholars in all subdisciplines that comprise cognitive science: psychology, computer science, neuroscience, linguistics, and philosophy.
Offers a new model of vocal tract articulation that explains laryngeal and oral voice quality, both auditorily and visually, through language examples and familiar voices.
The SAGE Encyclopedia of Human Communication Sciences and Disorders is an in-depth encyclopedia aimed at students interested in interdisciplinary perspectives on human communication—both normal and disordered—across the lifespan. This timely and unique set will look at the spectrum of communication disorders, from causation and prevention to testing and assessment; through rehabilitation, intervention, and education. Examples of the interdisciplinary reach of this encyclopedia: A strong focus on health issues, with topics such as Asperger's syndrome, fetal alcohol syndrome, anatomy of the human larynx, dementia, etc. Including core psychology and cognitive sciences topics, such as social development, stigma, language acquisition, self-help groups, memory, depression, memory, Behaviorism, and cognitive development Education is covered in topics such as cooperative learning, special education, classroom-based service delivery The editors have recruited top researchers and clinicians across multiple fields to contribute to approximately 640 signed entries across four volumes.
Measuring Voice, Speech, and Swallowing in the Clinic and Laboratory provides a definitive reference and text for methods of measurement of voice, speech, and swallowing functioning and disorders. It was developed for measurement courses in speech-language pathology graduate and doctoral programs and is also an essential reference for practitioners or anyone who needs to make quantitative assessments of the systems involved. The goal of this text is to provide basic information on the instruments and measures commonly used for assessing and treating persons with disorders of voice, speech, and swallowing for clinical practice, research studies, and conducting clinical trials. New developments in electrical and magnetic stimulation for noninvasive stimulation of nerves, muscles, and the brain are provided for augmenting treatment benefits for persons with voice, speech, and swallowing disorders. Other new techniques included are electromyography, articulography, transcranial magnetic stimulation, functional MRI, fNIRS, DTI, and transcranial direct current stimulation for treatment applications. The text includes methods for recording and analyzing speech, acoustics, imaging and kinematics of vocal tract motion, air pressure, airflow, respiration, clinical evaluation of voice and swallowing disorders, and functional and structural neuroimaging. Many of the methods are applicable for use in clinical practice and clinical research. Key Features: More than 250 full-color imagesSummary tables to guide selection of instruments and measures for various applicationsEach chapter begins and ends with an overview and conclusion for review of contentAppendices of measurement standards Clinical investigators and clinicians wanting to measure voice, speech, and swallowing functions for clinical documentation will benefit from this book, as will students and professors. Measuring Voice, Speech, and Swallowing in the Clinic and Laboratorypulls together the necessary information on methods of measurement from different disciplines and sources into one convenient resource. Information on measurement in the fields of voice, speech, and swallowing is now readily available for training doctoral students and guidance of clinicians incorporating instrumental assessment into their practice.
Shortlisted for the Christopher Brumfit Award in Applied Linguistics.The Development of the Grammatical System in Early Second Language Acquisition focuses on the acquisition process of early L2 learners. It is based on the following key hypothesis: the initial mental grammatical system of L2 learners is constrained semantically, syntactically and mnemonically. This hypothesis is formalised as the Multiple Constraints Hypothesis. The empirical test of the Multiple Constraints Hypothesis is based on a large database including cross-sectional and longitudinal data from square-one ESL beginners. The study demonstrates that the postulated constraints are relaxed successively as learning progresses. The book is intended for postgraduate students as well as SLA researchers.
This book constitutes the refereed proceedings of the 11th International Conference on Text, Speech and Dialogue, TSD 2008, held in Brno, Czech Republic, September 8-12, 2008. The 79 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 173 submissions. The topics of the conference include, but are not limited to, text corpora and tagging; transcription problems in spoken corpora; sense disambiguation; links between text and speech oriented systems; parsing issues; parsing problems in spoken texts; multi-lingual issues; multi-lingual dialogue systems; information retrieval and information extraction; text/topic summarization; machine translation; semantic networks and ontologies; semantic web; speech modeling; speech segmentation; speech recognition; search in speech for IR and IE; text-to-speech synthesis; dialogue systems; development of dialogue strategies; prosody in dialogues; emotions and personality modeling; user modeling; knowledge representation in relation to dialogue systems; assistive technologies based on speech and dialogue; applied systems and software; facial animation; and visual speech synthesis
Worldwide there is a universal need for second language language learning. It is obvious that the computer can be a great help for this, especially when equipped with methods for automatically assessing the learner's pronunciation. While assessment of segmental pronunciation quality (i.,e. whether phones and words are pronounced correctly or not) is already available in commercial software packages, prosody (i.e. rhythm, word accent, etc.) is largely ignored--although it highly impacts intelligibility and listening effort. The present thesis contributes to closing this gap by developing and analyzing methods for automatically assessing the prosody of non-native speakers. We study the detection of word accent errors and the general assessment of the appropriateness of a speaker's rhythm. We propose a flexible, generic approach that is (a) very successful on these tasks, (b) competitive to other state-of-the-art result, and at the same time (c) flexible and easily adapted to new tasks.
This is an open access book. The first international Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022) is a biennial conference organized by Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MS) India, during August 1–2, 2022. ACVAIT 2022, is dedicated towards advances in the theme areas of Computer Vision, Image Processing, Pattern Recognition, Artificial Intelligence, Machine Learning, Human Computer Interactions, Biomedical Image Processing, Geospatial Technology, Hyperspectral image processing and allied technologies but not limited to. ACVAIT 2022, invites young and/or advanced researchers contributing in the theme area of the conference and also provide them platform for discussing their scientific contributions / research findings with the domain experts, exchange ideas with them and foster closer collaboration between members from the top universities / Higher Education Institutes (HEI). ACVAIT 2022, inviting domain specific work from research scholars, academician, machine learning & AI scientist, industry experts to contribute their scientific contribution in the following areas but not limited to. • Shape representation• Biometrics: face matching, iris recognition, footprint verification and many more.• Statistical, Structural and syntactic pattern recognition• Brain Computer Interface and Human Computer Interactions• Feature extraction and reduction• Biomedical Image Processing• Color and texture analysis• Speech analysis and understanding• Image segmentation• Speaker verification & Synthesis• Image compression, coding and encryption• Clustering and classification• Object recognition, scene understanding and video analytics• Machine learning algorithms • Image matching (pattern matching)• Extreme learning machine• Content based image retrieval and indexing• Artificial Intelligence Trends in Deep learning• Optical character recognition• Big data• Image & Video Forensics• Information retrieval• Pattern recognition and machine learning for Internet of Things• Data mining and Data Analytics• Pattern classification through Sensors• Pattern Recognition for Hyper Spectral Imaging• Satellite Image Processing
