This book investigates the development and application of statistical models for understanding and processing non-native speech. It addresses the challenges inherent in acoustic and linguistic variations present in the speech of non-native speakers, aiming to improve the performance of speech processing systems in such contexts. The work draws upon principles of machine learning and computational linguistics to build robust models.

The book is a technical monograph likely aimed at researchers and advanced students in speech processing and computational linguistics. Its focus on statistical modeling suggests a rigorous, data-driven approach to understanding non-native speech patterns. The subject matter points to a dense, specialist text that contributes to the academic discourse on accent adaptation and cross-lingual speech technologies.