Multigranular scale speech recognition: tehnological and cognitive view

We propose a Multigranular Automatic Speech Recognizer. The hypothesis is that speech signal contains information distributed on more different time scales. Many works from various scientific fields ranging from neurobiology to speech technologies, seem to concord on this assumption. In a broad sense, it seems that speech recognition in human is optimal because of a partial parallelization process according to which the left-to-right stream of speech is captured in a multilevel grid in which several linguistic analyses take place contemporarily. Our investigation aims, in this view, to apply these new ideas to the project of more robust and efficient recognizers

An Efficient Distribution of Labor in a Two Stage Robust Interpretation Process

Although Minimum Distance Parsing (MDP) offers a theoretically attractive solution to the problem of extragrammaticality, it is often computationally infeasible in large scale practical applications. In this paper we present an alternative approach where the labor is distributed between a more restrictive partial parser and a repair module. Though two stage approaches have grown in popularity in recent years because of their efficiency, they have done so at the cost of requiring hand coded repair heuristics. In contrast, our two stage approach does not require any hand coded knowledge sources dedicated to repair, thus making it possible to achieve a similar run time advantage over MDP without losing the quality of domain independence.Comment: 9 pages, 1 Postscript figure, uses aclap.sty and psfig.tex, In Proceedings of EMNLP 199

Robust semantic analysis for adaptive speech interfaces

The DUMAS project develops speech-based applications that are adaptable to different users and domains. The paper describes the project's robust semantic analysis strategy, used both in the generic framework for the development of multilingual speech-based dialogue systems which is the main project goal, and in the initial test application, a mobile phone-based e-mail interface

Robust Processing of Natural Language

Previous approaches to robustness in natural language processing usually treat deviant input by relaxing grammatical constraints whenever a successful analysis cannot be provided by ``normal'' means. This schema implies, that error detection always comes prior to error handling, a behaviour which hardly can compete with its human model, where many erroneous situations are treated without even noticing them. The paper analyses the necessary preconditions for achieving a higher degree of robustness in natural language processing and suggests a quite different approach based on a procedure for structural disambiguation. It not only offers the possibility to cope with robustness issues in a more natural way but eventually might be suited to accommodate quite different aspects of robust behaviour within a single framework.Comment: 16 pages, LaTeX, uses pstricks.sty, pstricks.tex, pstricks.pro, pst-node.sty, pst-node.tex, pst-node.pro. To appear in: Proc. KI-95, 19th German Conference on Artificial Intelligence, Bielefeld (Germany), Lecture Notes in Computer Science, Springer 199

Ubiquitous emotion-aware computing

Emotions are a crucial element for personal and ubiquitous computing. What to sense and how to sense it, however, remain a challenge. This study explores the rare combination of speech, electrocardiogram, and a revised Self-Assessment Mannequin to assess people’s emotions. 40 people watched 30 International Affective Picture System pictures in either an office or a living-room environment. Additionally, their personality traits neuroticism and extroversion and demographic information (i.e., gender, nationality, and level of education) were recorded. The resulting data were analyzed using both basic emotion categories and the valence--arousal model, which enabled a comparison between both representations. The combination of heart rate variability and three speech measures (i.e., variability of the fundamental frequency of pitch (F0), intensity, and energy) explained 90% (p < .001) of the participants’ experienced valence--arousal, with 88% for valence and 99% for arousal (ps < .001). The six basic emotions could also be discriminated (p < .001), although the explained variance was much lower: 18–20%. Environment (or context), the personality trait neuroticism, and gender proved to be useful when a nuanced assessment of people’s emotions was needed. Taken together, this study provides a significant leap toward robust, generic, and ubiquitous emotion-aware computing

An Efficient Implementation of the Head-Corner Parser

This paper describes an efficient and robust implementation of a bi-directional, head-driven parser for constraint-based grammars. This parser is developed for the OVIS system: a Dutch spoken dialogue system in which information about public transport can be obtained by telephone. After a review of the motivation for head-driven parsing strategies, and head-corner parsing in particular, a non-deterministic version of the head-corner parser is presented. A memoization technique is applied to obtain a fast parser. A goal-weakening technique is introduced which greatly improves average case efficiency, both in terms of speed and space requirements. I argue in favor of such a memoization strategy with goal-weakening in comparison with ordinary chart-parsers because such a strategy can be applied selectively and therefore enormously reduces the space requirements of the parser, while no practical loss in time-efficiency is observed. On the contrary, experiments are described in which head-corner and left-corner parsers implemented with selective memoization and goal weakening outperform `standard' chart parsers. The experiments include the grammar of the OVIS system and the Alvey NL Tools grammar. Head-corner parsing is a mix of bottom-up and top-down processing. Certain approaches towards robust parsing require purely bottom-up processing. Therefore, it seems that head-corner parsing is unsuitable for such robust parsing techniques. However, it is shown how underspecification (which arises very naturally in a logic programming environment) can be used in the head-corner parser to allow such robust parsing techniques. A particular robust parsing model is described which is implemented in OVIS.Comment: 31 pages, uses cl.st