Structural translation with synchronous tree adjoining grammars in VERBMOBIL

The VERBMOBIL project is developing a translation system that can assist a face-to-face dialogue between two non-native english speakers. Instead of having continiously speak english, the dialogue partners have the option to switch to their respective mother tongues (currently german or japanese) in cases where they can\u27t find the required word, phrase or sentence. In such situations, the users activate VERBMOBIL to translate their utterances into english. A very important requirement for such a system is realtime processing. Realtime processing is essentially necessary, if such a system is to be smoothly integrated into an ongoing communication. This can be achieved by the use of anytime processing, which always provides a result. The quality of the result however, depends on the computation time given to the system. Early interruptions can only produce shallow results. Aiming at such a processing mode, methods for fast but preliminary translation must be integrated into the system assisted by others that refine these results. In this case we suggest structural translation with Synchronous Tree Adjoining Grammars (S-TAGs), which can serve as a fast and shallow realisation of all steps necessary during translation, i.e. analysis, transfer and generation, in a system capable of running anytime methods. This mode is especially adequate for standardized speech acts and simple sentences. Furthermore, it provides a result for early interruptions of the translation process. By building an explicit linguistic structure, methods for refining the result can rearrange the structure in order to increase the quality of the translation given extended execution time. This paper describes the formalism of S-TAGs and the parsing algorithm implemented in VERBMOBIL. Furthermore the language covered by the german grammar is described. Finally we list examples together with the execution time required for their processing

Incremental generation for real-time applications

The acceptance of natural language generation systems strongly depends on their capability to facilitate the exchange of information with human users. Current generation systems consider the influence of situational factors on the content and the form of the resulting utterances. However, the need to time their processing flexibly is usually neglected although temporal factors play a central part when directly addressing a human communication partner. A short response time of a system is crucial for its effective use. Furthermore, some applications - e.g., the simultaneous description of ongoing events - even necessitate the interleaving of input consumption and output production, i.e. the use of an incremental processing mode. We claim that incremental processing is a central design principle for developing flexible and efficient generators for speech output. We discuss the advantages of parallel processing for incremental generation and several aspects of control of the generator. An extension of Tree Adjoining Grammar is introduced as an adequate representation formalism for incremental syntactic generation. We present the system VM-GEN - an incremental and parallel syntactic generator based on Tree Adjoining Grammars. It offers flexible input and output interfaces that are adaptable to the requirements of the surrounding system by coping with varying sizes of input and output increments. The system's ability to produce fluent speech is a step towards approximating human language performance

Interpretación tabular de autómatas para lenguajes de adjunción de árboles

[Resumen] Las gramáticas de adjunción de árboles son una extensión de las gramáticas independientes del contexto que utilizan árboles en vez de producciones como estructuras elementales y que resultan adecuadas para la descripción de la mayor parte de las construcciones sintácticas presentes en el lenguaje natural. Los lenguajes generados por esta clase de gramáticas se denominan lenguajes de adjunción de árboles y son equivalentes a los lenguajes generados por las gramáticas lineales de índices y otros formalismos suavemente dependientes del contexto. En la primera parte de esta memoria se presenta el problema del análisis sintáctico de los lenguajes de adjunción de árboles. Para ello, se establece un camino evolutivo continuo en el que se sitúan los algoritmos de análisis sintáctico que incorporan las estrategias de análisis más importantes, tanto para el caso de las gramáticas de adjunción de árboles como para el caso de las gramáticas lineales de índices. En la segunda parte se definen diferentes modelos de autómata que aceptan exactamente los lenguajes de adjunción de árboles y se proponen técnicas que permiten su ejecución eficiente. La utilización de autómatas para realizar el análisis sintáctico es interesante porque permite separar el problema de la definición de un algoritmo de análisis sintáctico del problema de la ejecución del mismo, al tiempo que simplifica las pruebas de corrección. Concretamente, hemos estudiado los siguientes modelos de autómata: • Los autómatas a pila embebidos descendentes y ascendentes, dos extensiones de ^ los autómatas a pila que utilizan como estructura de almacenamiento una pila de pilas. Hemos definido nuevas versiones de estos autómatas en las cuales se simplifica la forma de las transiciones y se elimina el control de estado finito, manteniendo la potencia expresiva. • La restricción de los autómatas lógicos a pila para adaptarlos al reconocimiento de las gramáticas lineales de índices, obteniéndose diferentes tipos de autómatas especializados en diversas estrategias de análisis según el conjunto de transiciones permitido. • Los autómatas lineales de índices, tanto los orientados a la derecha, adecuados para estrategias en las cuales las adjunciones se reconocen de manera ascendente, los orientados a la izquierda, aptos para estrategias de análisis en las que las adjunciones se tratan de forma descendente, como los fuertemente dirigidos, capaces de incorporar estrategias de análisis en las cuales las adjunciones se tratan de manera ascendente y/o descendente. • Los autómatas con dos pilas, una extensión de los autómatas a pila que trabaja con una pila maestra encargada de dirigir el proceso de análisis y una pila auxiliar que restringe las transiciones aplicables en un momento dado. Hemos descrito dos versiones diferentes de este tipo de autómatas, los autómatas con dos pilas fuertemente dirigidos, aptos para describir estrategias de análisis arbitrarias, y los autómatas con dos pilas ascendentes, adecuados para describir estrategias de análisis en las cuales las adjunciones se procesan ascendentemente. Hemos definido esquemas de compilación para todos estos modelos de autómata. Estos esquemas permiten obtener el conjunto de transiciones correspondiente a la implantación de una determinada estrategia de análisis sintáctico para una gramática dada. Todos los modelos de autómata pueden ser ejecutados en tiempo polinomial con respecto a la longitud de la cadena de entrada mediante la aplicación de técnicas de interpretación tabular. Estas técnicas se basan en la manipulación de representaciones colapsadas de las configuraciones del autómata, denominadas ítems, que se almacenan en una tabla para su posterior reutilización. Con ello se evita la realización de cálculos redundantes. Finalmente, hemos analizado conjuntamente los diferentes modelos de autómata, los cuales se pueden dividir en tres grandes grupos: la familia de los autómatas generales, de la que forman parte los autómatas lineales de índices fuertemente dirigidos y los autómatas con dos pilas fuertemente dirigidos; la familia de los autómatas descendentes, en la que se encuadran los autómatas a pila embebidos y los autómatas lineales de índices orientados a la izquierda; y la familia de los autómatas ascendentes, en la que se enmarcan los autómatas a pila embebidos ascendentes, los autómatas lineales de índices orientados a la derecha y los autómatas con dos pilas ascendentes.[Abstract] Tree adjoining grammars are an extension of context-free grammars that use trees instead of productions as the primary representing structure and that are considered to be adequate to describe most of syntactic phenomena occurring in natural languages. These grammars generate the class of tree adjoining languages, which is equivalent to the class of languages generated by linear indexed grammars and other mildly context-sensitive formalisms. In the first part of this dissertation, we introduce the problem of parsing tree adjoining grammars and linear indexed grammars, creating, for both formalisms, a continuum from simple pure bottom-up algorithms to complex predictive algorithms and showing what transformations must be applied to each one in order to obtain the next one in the continuum. In the second part, we define several models of automata that accept the class of tree adjoining languages, proposing techniques for their efficient execution. The use of automata for parsing is interesting because they allow us to separate the problem of the definition of parsing algorithms from the problem of their execution. We have considered the following types of automata: • Top-down and bottom-up embedded push-down automata, two extensions of push-down automata working on nested stacks. A new definition is provided in which the finite-state control has been eliminated and several kinds of normalized transition have been defined, preserving the equivalence with tree adjoining languages. • Logical push-down automata restricted to the case of tree adjoining languages. Depending on the set of allowed transitions, we obtain three different types of automata. • Linear indexed automata, left-oriented and right-oriented to describe parsing strategies in which adjuntions are recognized top-down and bottom-up, respectively, and stronglydriven to define parsing strategies recognizing adjunctions top-down and/or bottom-up. • 2-stack automata, an extension of push-down automata working on a pair of stacks, a master stack driving the parsing process and an auxiliary stack restricting the set of transitions that can be applied at a given moment. Strongly-driven 2-stack automata can be used to describe bottom-up, top-down or mixed parsing strategies for tree adjoining languages with respect to the recognition of the adjunctions. Bottom-up 2-stack automata are specifically designed for parsing strategies recognizing adjunctions bottom-up. Compilation schemata for these models of automata have been defined. A compilation schema allow us to obtain the set of transitions corresponding to the implementation of a^ parsing strategy for a given grammar. All the presented automata can be executed in polynomial time with respect to the length of the input string by applying tabulation techniques. A tabular technique makes possible to interpret an automaton by means of the manipulation of collapsed representation of configurations (called items) instead of actual configurations. Items are stored into a table in order to be reused, avoiding redundant computations. Finally, we have studied the relations among the diíferent classes of automata, the main dif%rence being the storage structure used: embedded stacks, indices lists or coupled stacks. According to the strategies that can be implemented, we can distinguish three kinds of automata: bottom-up automata, including bottom-up embedded push-down automata, bottomup restricted logic push-down automata, right-oriented linear indexed automata and bottom-up 2-stack automata; top-down automata, including (top-down) embedded push-down automata, top-down restricted logic push-down automata and left-oriented linear indexed automata; and general automata, including strongly-driven linear indexed automata and strongly-driven 2- stack automata

Fifth Conference on Artificial Intelligence for Space Applications

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