SCREEN: Learning a Flat Syntactic and Semantic Spoken Language Analysis Using Artificial Neural Networks

In this paper, we describe a so-called screening approach for learning robust processing of spontaneously spoken language. A screening approach is a flat analysis which uses shallow sequences of category representations for analyzing an utterance at various syntactic, semantic and dialog levels. Rather than using a deeply structured symbolic analysis, we use a flat connectionist analysis. This screening approach aims at supporting speech and language processing by using (1) data-driven learning and (2) robustness of connectionist networks. In order to test this approach, we have developed the SCREEN system which is based on this new robust, learned and flat analysis. In this paper, we focus on a detailed description of SCREEN's architecture, the flat syntactic and semantic analysis, the interaction with a speech recognizer, and a detailed evaluation analysis of the robustness under the influence of noisy or incomplete input. The main result of this paper is that flat representations allow more robust processing of spontaneous spoken language than deeply structured representations. In particular, we show how the fault-tolerance and learning capability of connectionist networks can support a flat analysis for providing more robust spoken-language processing within an overall hybrid symbolic/connectionist framework.Comment: 51 pages, Postscript. To be published in Journal of Artificial Intelligence Research 6(1), 199

Re-verification of a Lip Synchronization Protocol using Robust Reachability

The timed automata formalism is an important model for specifying and analysing real-time systems. Robustness is the correctness of the model in the presence of small drifts on clocks or imprecision in testing guards. A symbolic algorithm for the analysis of the robustness of timed automata has been implemented. In this paper, we re-analyse an industrial case lip synchronization protocol using the new robust reachability algorithm. This lip synchronization protocol is an interesting case because timing aspects are crucial for the correctness of the protocol. Several versions of the model are considered: with an ideal video stream, with anchored jitter, and with non-anchored jitter

Re-verification of a Lip Synchronization Algorithm using robust reachability

The timed automata formalism is an important model for specifying and analysing real-time systems. Robustness is the correctness of the model in the presence of small drifts on clocks or imprecision in testing guards. A symbolic algorithm for the analysis of the robustness of timed automata has been implemented. In this paper we re-analyse an industrial case lip synchronization protocol using the new robust reachability algorithm.This lip synchronization protocol is an interesting case because timing aspect are crucial for the correctness of the protocol. Several versions of the model are considered, with an ideal video stream, with anchored jitter, and with non-anchored jitter

Spoken language processing in the hybrid connectionist architecture SCREEN

In this paper we describe a robust, learning approach to spoken language understanding. Since interactively spoken and computationally analyzed language often contains many errors, robust connectionist networks are used for providing a flat screening analysis. A screening analysis is a shallow flat analysis based on category sequences at various syntactic, semantic and dialog levels. Rather than using tree or graph representations a screening analysis uses category sequences in order to support robustness and learning. This flat screening analysis is examined in the context of the system SCREEN (Symbolic Connectionist Robust EnterprisE for Natural language). Starting with the word hypotheses generated by a speech recognizer, we give an overview of the architecture, and illustrate the flat robust processing at the levels of syntax, semantics, and dialog acts. While early connectionist models were often limited to a single network and a small task, the hybrid connectionist SCREEN system is an important step towards exploring connectionist techniques in larger hybrid symbolic/connectionist environments and for real-world problemsBased on our experience with SCREEN, hybrid connectionist techniques show a lot of potential for supporting robustness in interactive spoken language processing