The authors give a detailed account of a system environment for treating general problems of image and speech understanding. A framework for representing declarative and procedural knowledge based on a suitable definition of a semantic network is provided. The syntax and semantics of the network are clearly defined. The pragmatics of the network in its use for pattern understanding are defined by several rules which are problem-independent. This allows one to formulate problem-independent control algorithms. Complete software environments are available to handle the described structures. The general applicability of the network system is demonstrated by short descriptions of three applications from different task domains. >

/pdf/ernest-a-semantic-network-system-for-pattern-understanding-5auky8mswo.pdf

ERNEST: a semantic network system for pattern understanding

Bei dem vorliegenden Aufsatz handelt es sich um eine einfuhrende Darstellung wichtiger Fragestellungen, Methoden und Resultate des Forschungsgebietes ‘Naturlichsprachliche Systeme’. Die Komplexitat und die Breite des zu behandelnden Teilgebietes der Kunstlichen Intelligenz (Kl) machen es unmoglich, in einer kurzen Einfuhrung auch nur annahernd alle fur die sprachorientierte Kl-Forschung relevanten Fragestellungen und Losungsalternativen aufzuzeigen (z.B. umfast alleine eine grundliche Einfuhrung in die syntaktische Analyse, wie sie Winograd 1983 bietet, rd. 640 Seiten). Dies mag auch als Grund dafur angesehen werden, das Standardeinfuhrungen in die Kunstliche Intelligenz wie Winston 1977 und Nilsson 1981 das Teilgebiet ‘Naturlichsprachliche Systeme’ nicht in angemessener Weise behandeln.

Natürlichsprachliche Systeme - Eine Einführung in die sprachorientierte KI-Forschung

We present the semantics component of a speech understanding and dialogue system that is developed at our institute. Due to pronunciation variabilities and vagueness of the word recognition process, semantics in a speech understanding system has to resolve additional problems. Its main task is not only to build up a representation structure for the meaning of an utterance, as in a system for written input, semantic knowledge is also employed to decide between alternative word hypotheses, to judge the plausibility of syntactic structures, and to guide the word recognition process by expectations resulting from partial analyses.

The role of semantic processing in an automatic speech understanding system

Based on a detained discussion of system architectures for knowledge based speech understanding and knowledge representation techniques, criteria for both a knowledge representation scheme and system architectures are developed. Upon this background a system is introduced which is organized around a homogenuous knowledge base. Both the knowledge representation language and the content of the knowledge base are described. The knowledge representation language do not only cover declarative but also procedural knowledge. Analysis processes are guided by a flexibel bottom-up top-down strategy. Besides the procedural semantics of the language the A -Algorithm is used for this purpose. Search graph nodes are judged by a vector which reflects knowledge dependent and acoustic scores and which is admissable for the A -Algorithm.

/pdf/knowledge-based-systems-for-speech-understanding-1hvruial4k.pdf

Knowledge based systems for speech understanding

This contribution describes an approach to integrate a speech understanding and dialog system into a homogeneous architecture based on semantic networks. The definition of the network as well as its use in speech understanding is described briefly. A scoring function for word hypotheses meeting the requirements of a graph search algorithm is presented. The main steps of the linguistic analysis, i.e. syntax, semantics, and pragmatics, are described and their realization in the semantic network is shown. The processing steps alternating between data- and model-driven phases are outlined using an example sentence which demonstrates a tight interaction between word recognition and linguistic processing.

/pdf/the-interaction-of-word-recognition-and-linguistic-37hu3amsol.pdf

The Interaction of Word Recognition and Linguistic Processing in Speech Understanding

This paper gives an overview of a research effort whose goal is to develop a system which can carry out a dialog concerning a particular task domain using continuous German speech for input and output. The main processing phases are initial segmentation and labeling, finding words, understanding the meaning and giving an answer. Specialized processing modules for handling these four phases were developed or are being developed. The processing modules communicate via a common database.

The speech understanding and dialog system EVAR

A system for understanding continuous German speech

The system developed at the University of Erlangen for continuous speech understanding consists of a set of specialized independent modules operating on a common data base under the supervision of a control module. Speech quality is limited to telephone band width, the size of the vocabulary presently is about 1300 words, and syntactic, semantic, and pragmatic constraints are used. The paper describes the present status of the system, in particular the modules which are operational now; and it mentions the modules which are still in the development stage.

The Erlangen system for understanding continuous German speech

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The speech understanding and dialog system EVAR

A system for understanding continuous German speech

The Erlangen system for understanding continuous German speech