Bilingual Response Generation using Semi-Automatically- Induced Templates for a Mixed-Initiative Dialog System

We have previously developed a framework for natural language response generation for mixed-initiative dialogs in the CUHK Restaurants domain [I]. This paper investigates the use of semi-automatic technique for response templates generation. We adopt a semi-automatic approach for grammar induction [2] to capture the language structures of responses from unannotated corpora. We wish to use this approach to induce a set of grammars from our response data. The induced grammars are coupled with a parser to produce response templates in a semi-automatic way. Our response data consists of 2349 waiter responses. It is used as the training corpus for grammar induction. Unsupervised grammar induction is first performed, followed by using the learned grammars as prior knowledge for seeding the clustering process. Results show that the semi-automatically-induced response templates cover more than 50 % of the hand-designed templates in templates coverage and provide more realization options: Performance evaluation indicates that the task completion rate has at least 90%. and most of the Grice’s maxims as well as the overall user satisfaction scored at 3.5 points or above. training corpus for grammar induction. We perform unsupervised grammar induction first and use the learned grammars as prior knowledge for seeding the clustering process. A set of semi-automatically-induced response templates can then derived by parsing our response data with the induced grammars. 2. THE RESPONSE DATA Our response data contains 2349 waiter response utterances which are mainly extracted from the CUHK Restaurants corpus [I]. The corpus contains 260 dialogs (with 1785 customer request utterances and 2176 waiter response utterances) that capture interactions between a customer and a waiter in a restaurant. We use those waiter response utterances from the corpus and further expand ow response data by collecting 173 waiter response utterances from bwks [3, 4, 5, 61. Some “Do you have a reservation?” “How c4n I help you? ’’ “I wuld recommend smoked salmon scallop. ” 1

Bilingual Response Generation using Semi-Automatically- Induced Templates for a Mixed-Initiative Dialog System

We have previously developed a framework for natural language response generation for mixed-initiative dialogs in the CUHK Restaurants domain [1]. This paper investigates the use of semi-automatic technique for response templates generation. We adopt a semi-automatic approach for grammar induction [2] to capture the language structures of responses from unannotated corpora. We wish to use this approach to induce a set of grammars from our response data. The induced grammars are coupled with a parser to produce response templates in a semi-automatic way. Our response data consists of 2349 waiter responses. It is used as the training corpus for grammar induction. Unsupervised grammar induction is first performed, followed by using the learned grammars as prior knowledge for seeding the clustering process. Results show that the semi-automatically-induced response templates cover more than 50 % of the hand-designed templates in templates coverage and provide more realization options. Performance evaluation indicates that the task completion rate has at least 90%, and most of the Grice’s maxims as well as the overall user satisfaction scored at 3.5 points or above. 1