Fitsum S Alemu

This research attempts to propose an approach to make decisions under uncertainty for designing a dialogue manager for Amharic spoken dialogue system, Amharic as under-resourced language. A prototype Amharic Spoken Dialogue System was implemented on hotel and restaurant address information domain for experimentation. Data for this research was collected through a method called Wizard of Oz and domain knowledge is prepared using address search websites. How to design a dialogue manager which is robust for languages especially with low performing Automatic Speech Recognition unit is a fundamental question of this research. Previous studies on designing of spoken dialogue system for under resourced languages focused mainly on Automatic Speech Recognizer. We reviewed methods and frameworks on dialogue management. Design of Partially Observable Markov Decision Processes (POMDP) based dialogue manager, which provides a principled framework to plan under uncertainty, yields robustness. Low performing Spoken Dialogue System (SDS) components, especially the Automatic Speech Recognizer (ASR) were considered the causes of uncertainty. Maintaining multiple hypotheses (evidences) improves the correctness of the dialogue manager. We conducted experiments to test correctness score, error rate and robustness. With a maximum of 6 N-best list and 20 partitions the correctness score grow by 14.19%. Increasing the number of n-best list of 6 reduced the error rate by 5.78% and with 6 n-best list. The belief updated below 0.12 seconds with 20 partitions and 6-nbest list. And the dialogue manager was able to complete a task with an average 8.75 turns by 50% Word Error Rate. The finding from the research illustrates that POMDP-based design approach to dialogue management is robust and possible to develop an improving spoken dialogue system for under-resourced languages.