39. Principles of Spoken Language Recognition

In this introductory chapter to Part G of this Handbook on spoken language recognition, we provide a brief overview of the principles of state-ofthe-art language recognition approaches, and a general discriminative training framework to improve the performance and robustness of language recognition systems. It is followed by three chapters. The first of these addresses issues related to spoken language characterization in which knowledge sources can be utilized to distinguish one language from another. The second chapter deals with language identification based on phone recognition followed by language modeling using either spectral or token-based approaches. The third chapter presents vector-space characterization approaches to converting speech utterances into spoken document vectors for modeling and classification. With recent progress in speech processing, machine learning, and text categorization, we expect significant technology advances in spoken language recognition in the years to come. This chapter is organized as follows. Section 39.2 briefly describes the principle of spoken 39.1 Spoken Language ................................. 785