Portability challenges in developing interactive dialogue systems

Statistical methods commonly used in developing interactive dialogue systems require large amounts of training data to achieve high accuracy and robustness. This becomes a major bottleneck in building free-style dialogue systems in a new domain or for a new language. Portability challenges hence arise regarding how to build statistical models rapidly and with low cost in terms of data collection, transcription and annotation. In this paper, we discuss challenges as well as potential solutions in several critical issues of efficient language modeling, utilization of untranscribed speech data, automatic annotation, and cross-lingual modeling. We believe that current approaches in these areas are far from mature and call for serious efforts from the research community.