The estimation of initial language models for new applications of spoken dialogue systems without large taskspecific training corpora is becoming an increasingly important issue. This paper investigates two different approaches in which the task-specific knowledge contained in the language understanding grammar is exploited in order to generate n-gram language models for the speech recognizer: ...

In this paper we present a computer assisted language learning (CALL) system that is developed to practice grammar in spoken language. To enable this, the system uses Automatic Speech Recognition (ASR) to process the L2 learner’s responses. We investigate the possibility of providing corrective feedback (CF) on learner errors, and compare that with self-monitored language learning through outpu...

We are interested in constructing machines which learn to understand and act upon fluently spoken input. For any particular task, certain linguistic events are critical to recognize correctly, others not so. This notion can be quantified via salience, which measures the information content of an event for a task. In previous papers, salient words have been exploited to learn the mapping from sp...

The availability of digital maps and mapping software has led to significant growth in location-based software and services. To safely use these applications in mobile and automotive scenarios, users must be able to input precise locations using speech. In this paper, we propose a novel method for location understanding based on spoken intersections. The proposed approach utilizes a rich, autom...

We will demonstrate the latest version of an ongoing project to create an intelligent procedure assistant for use by astronauts on the International Space Station (ISS). The system functionality includes spoken dialogue control of navigation, coordinated display of the procedure text, display of related pictures, alarms, and recording and playback of voice notes. The demo also exemplifies sever...

This paper describes the integration of an LR natural language parser with the SPHINX speech recognition system. SPHINX is one of the most successful speech recognition systems in use today. Although it attains high word accuracy, SPHINX often outputs ungrammatical recognition results because the baseline SPHINX system uses very simple word-pair or bigram language models. For applications of sp...

In this paper, we propose a new approach for acquiring translation templates automatically from unannotated bilingual spoken language corpora. Two basic algorithms are adopted: a grammar induction algorithm, and an alignment algorithm using Bracketing Transduction Grammar. The approach is unsupervised, statistical, data-driven, and employs no parsing procedure. The acquisition procedure consist...

In complex grammars, even small changes may have an unforeseeable impact on overall system performance. As grammar based systems are increasingly deployed for industrial and other large-scale applications, it is imperative to have systematic regression testing in place. Systematic testing in grammar-based systems serves several purposes. It helps developers to track progress, and to recognize a...

Grammar-based approaches to spoken language understanding are utilized to a great extent in industry, particularly when developers are confronted with data sparsity. In order to ensure wide grammar coverage, developers typically modify their grammars in an iterative process of deploying the application, collecting and transcribing user utterances, and adjusting the grammar. In this paper, we ex...

In this paper, we describe and evaluate an Open Source medical speech translation system (MedSLT) intended for safety-critical applications. The aim of this system is to eliminate the language barriers in emergency situation. It translates spoken questions from English into French, Japanese and Finnish in three medical subdomains (headache, chest pain and abdominal pain), using a vocabulary of ...