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Through efforts over the past fifteen years, we have acquired a great deal of experience in designing spoken dialogue systems that provide access to large corpora of data in a variety of different knowledge domains, such as flights, hotels, restaurants, weather, etc. In our recent research, we have begun to shift our focus towards developing tools that(More)
We have designed, implemented and evaluated an end-to-end system spellcheck-ing and autocorrection system that does not require any manually annotated training data. The World Wide Web is used as a large noisy corpus from which we infer knowledge about misspellings and word usage. This is used to build an error model and an n-gram language model. A small(More)
We describe a novel hierarchical duration model for speech recognition. The modelling scheme is based on the angie framework, a exible uniied sublexical representation for speech applications. Our duration model captures con-textual factors that innuence duration of sublexical units at multiple linguistic levels simultaneously, using both relative and(More)
Mixed-initiative spoken dialogue systems today generally allow users to query with a fixed vocabulary and grammar that is determined prior to run-time. This paper presents a spoken dialogue interface enhanced with a dynamic vocabulary capability. One or more word classes can be made dynamic in the speech recognizer and natural language (NL) grammar so that(More)
This paper describes a novel multi-stage recognition procedure for deducing the spelling and pronunciation of an open set of names. The overall goal is the automatic acquisition of unknown words in a human computer conversational system. The names are spoken and spelled in a single utterance, achieving a concise and natural dialogue flow. The first(More)
In this work we report our efforts to facilitate the creation of mixed-initiative conversational interfaces for novice and experienced developers of human language technology. Our focus has been on a framework that allows developers to easily specify the basic concepts of their applications, and rapidly prototype conversational interfaces for a variety of(More)
When building a new spoken dialogue application , large amounts of domain specific data are required. This paper addresses the issue of generating in-domain training data when little or no real user data are available. The two-stage approach taken begins with a data induction phase whereby linguistic constructs from out-of-domain sentences are harvested and(More)
This paper explores some issues in designing conversational systems with integrated higher level constraints. We experiment with a configuration that combines a context-dependent acoustic front-end, using MIT's SUMMIT recognizer, with ANGIE, a hierarchical framework that models word substructure and phono-logical processes, and with TINA, a trainable(More)