Second Language Prosody and Computer Modeling
About this ebook
The book illustrates the growing importance of the relationship between automated speech recognition systems and language learning assessment in light of new technologies and showcases how the study of prosody in this context in particular can offer innovative insights into the computerized process of natural discourse. The book offers detailed accounts of different methods of analysis and computer models used and demonstrates how these models can be applied to L2 discourse analysis toward predicting real-world language use. Kang, Johnson, and Kermad also use these frameworks as a jumping-off point from which to propose new models of second language prosody and future directions for prosodic computer modeling more generally.
Making the case for the use of naturalistic data for real-world applications in empirical research, this volume will foster interdisciplinary dialogues across students and researchers in applied linguistics, speech communication, speech science, and computer engineering.
About the author
Okim Kang is Professor of Applied Linguistics and Director of the Applied Linguistics Speech Lab at Northern Arizona University, Flagstaff, AZ. Her research interests include speech production and perception, L2 pronunciation and intelligibility, L2 oral assessment and testing, automated scoring and speech recognition, World Englishes, and language attitude.
David O. Johnson is an associate teaching professor of Electrical Engineering and Computer Science at the University of Kansas. His research interests are in artificial intelligence, machine learning, natural language processing, and human-robot interaction.
Alyssa Kermad is an assistant professor of Applied Linguistics and TESOL at California State Polytechnic University, Pomona. Her research interests are in second language speech and pronunciation, speech perception, prosody and pragmatics, second language acquisition, individual differences, and speech assessment.
