This paper presents a set of mathematical and computational tools for manipulating and reasoning about regular languages and regular relations and argues that they provide a solid basis for computational phonology It shows in detail how this framework applies to ordered sets of context-sensitive rewriting rules and also to grammars in Koskenniemi's two-level formalism This analysis provides a common representation of phonological constraints that supports efficient generation and recognition by a single simple interpreter

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Regular models of phonological rule systems

A speech recognition technique uses lexical tree pre-filtering to obtain lists of words for use in performing speech recognition. The lexical tree pre-filtering includes representing a vocabulary of words using a lexical tree and identifying a first subset of the vocabulary that may correspond to speech spoken beginning at a first time by propagating through the lexical tree information about the speech spoken beginning at the first time. A second subset of the vocabulary that may correspond to speech spoken beginning at a second time is identified by propagating through the lexical tree information about the speech spoken beginning at the second time. Words included in the speech are recognized by comparing speech spoken beginning at the first time with words from the first subset of the vocabulary and speech spoken beginning at the second time with words from the second subset of the vocabulary. The state of the lexical tree is not reset between identifying the first and second subsets.

Lexical tree pre-filtering in speech recognition

A generalization of the notion of ATN grammar, called a cascaded ATN (CATN), is presented. CATN's permit a decomposition of complex language understanding behavior into a sequence of cooperating ATN's with separate domains of responsibility, where each stage (called an ATN transducer) takes its input from the output of the previous stage. The paper includes an extensive discussion of the principle of factoring -- conceptual factoring reduces the number of places that a given fact needs to be represented in a grammar, and hypothesis factoring reduces the number of distinct hypotheses that have to be considered during parsing.

Cascaded ATN grammars

The availability of low-cost interactive computing for commercial applications makes it attractive to give end-users direct access to computers in a “conversational” mode. The need to minimize typing by the user leads to the conversational dialogues consisting of a series of “prompts” and responses. Such dialogue sequences are now being programmed into a wide range of systems, but there are currently available only limited guidelines on appropriate programming techniques. This paper expresses the view that the programming of interactive dialogue is an important technology for software engineering in its own right. It develops systematically a set of “rules” for dialogue programming and discusses them in terms of user psychology. It is hoped that this definitive approach will lead to additions, extensions, and refinements, to these rules, eventually generating a recognized technology for dialogue engineering .

The technology of interaction—dialogue programming rules

Parsing spoken input introduces serious problems not present in parsing typed natural language. In particular, indeterminacies and inaccuracies of acoustic recognition must be handled in an integral manner. Many techniques for parsing typed natural language do not adapt well to these extra demands. This paper describes an extension of semantic caseframe parsing to restricted-domain spoken input. The semantic caseframe grammar representation is the same as that used for earlier work on robust parsing of typed input. Due to the uncertainty inherent in speech recognition, the caseframe grammar is applied in a quite different way, emphasizing island growing from caseframe headers. This radical change in application is possible due to the high degree of abstraction in the caseframe representation. The approach presented was tested successfully in a preliminary implementation.

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Parsing spoken language: a semantic caseframe approach

Speech understanding systems

Uses of higher level knowledge in a speech understanding system: A progress report

: Contents: Natural Communication with a Computer; Types of Knowledge Needed; Representations and Processing; Travel Budget Management; Flow of Control; Parsing; Semantic Interpretation; SEMNET - The Network Utility Package; Command Language; Data Base Structure; Discourse Model; Text Response Generation; and Speech Synthesis.

J. W. Klovstad

Papers

Speech understanding systems

Uses of higher level knowledge in a speech understanding system: A progress report

Speech understanding systems. Volume 5: Trip