Abstract: An automated system generates and revises grammars for speech recognizers in a speech recognition system. Given an initial grammar, expressed in terms of non-terminals in Backus-Naur Form (BNF) notation, a sentence generator generates a list of all sentences accepted by the grammar. From this list, a corpus of inappropriate or irrelevant sentences which are accepted by the grammar (counter-examples) is identified. A grammar revisor program uses the original grammar and the list of counter examples, to generate a pruned list from which a revised grammar is generated. The revision process is iterated several times either concatenating or merging pairs of non-terminals until the revised grammar is deemed satisfactory in that it accepts as legal only relevant sentences. The revised grammar is used by the speech recognizer, thus reducing errors in the overall system.

Abstract: A computer system has a document collection of one or more documents and one or more indexes that each include an inverted file with one or more terms. Each of the terms is associated with one or more document identifiers. The index further includes a document catalog that associates each of the document identifiers with one or more attributes, either intrinsic or non intrinsic. A search engine process produces a hit list having one or more hit list entries. Each hit list entry, with one or more hit list attributes, is associated with one of the documents that is determined by the search engine to be relevant to the query. A formatter processor selects one or more of the hit list attributes, identified by a hit list attribute selector and then compares the selected attributes of two or more entries on the hit list to determine whether or not documents associated with these entries are duplicate instances of one another.