In this paper, we describe a system which is capable of utilizing a variety of knowledge sources to select the most appropriate parse for a spoken sentence. These knowledge sources include syntax, semantics, and contextual information. We discuss one way to utilize contextual information when determining the parse for a sentence. At its simplest level, the system can be thought of as a generalpurpose query answering system for multiple topical databases. The user's input would be processed by the language processor which interfaces to the databases with the goal of interacting with the correct database in order to provide a reasonable answer to the user's spoken request. Initially, it analyzes a word graph of sentence hypotheses provided by a speech recognizer using general syntactic and semantic rules. Then, if the utterance is still ambiguous, it utilizes contextspecific constraints to further refine the analysis. This brings us closer to developing a more general purpose interface f...

This paper describes the parallelization of Constraint Dependency Grammar (CDG) parsing. Though CDG provides a flexible framework for text-based and spoken language parsing and has an expressivity strictly greater than context-free grammars (CFGs), it also has a relatively slow serial running time (i.e., O(n 4 )). However, a parallelization for this algorithm is derived which uses O(n 4 ) processors to parse in O(k) time for a CRCW P-RAM, where n is the number of words in the sentence and k, the number of constraints, is a grammatical constant. Additionally, the paper describes an implementation of the algorithm on the MasPar MP-1, which uses the special features of the machine (particularly the global router) and O(n 4 ) processors to obtain an O(k + log(n)) running time. Because the average length of an English sentence is on the order of 10 words, the MasPar MP-1 has sufficient processors (i.e., 16,000) for parsing a typical sentence. Previous work in parallel parsing has fo...

This paper describes the implementation of a constraint-based parser, PARSEC (Parallel ARchitecture SEntence Constrainer), which has the required flexibility that a user may easily construct a custom grammar and test it. Once the user designs grammar parameters, constraints, and a lexicon, our system checks them for consistency and creates a parser for the grammar. The parser has an X-windows interface that allows a user to view the state of a parse of a sentence, test new constraints, and dump the constraint network to a file. The parser has an option to perform the computationally expensive constraint propagation steps on the MasPar MP-1. Stream and socket communication was used to interface the MasPar constraint parser with a standard X-windows interface on our Sun Sparcstation