Other Challenges: Non-native Speech, Dialects, Accents, and Local Interfaces

This chapter focuses on problems posed by non-native speech input as well as accent and dialect variation with respect to acoustic modeling, dictionaries, and language modeling in speech recognition systems. It begins with a description of the manifold characteristics of non-native speech. This includes theoretical models and descriptions obtained from corpus analysis along with a description of non-native databases. Almost all investigations in non-native speech require non-native speech data. Obtaining sufficient non-native speech data is one of the biggest problems. While there are plenty of databases for many different languages, they usually contain only native speech data. Very few databases containing non-native speech are publicly available. Speaker adaptation techniques have proven valuable for adapting acoustic models (AMs) to both native and nonnative speakers. This chapter describes speaker adaptation techniques in the special context of non-native speakers, and discusses pragmatic strategies, such as handling code-switching, and the design of voice-based user interfaces for speakers with different cultural backgrounds.