268 research outputs found
A Robust and Efficient Three-Layered Dialogue Component for a Speech-to-Speech Translation System
We present the dialogue component of the speech-to-speech translation system
VERBMOBIL. In contrast to conventional dialogue systems it mediates the
dialogue while processing maximally 50% of the dialogue in depth. Special
requirements like robustness and efficiency lead to a 3-layered hybrid
architecture for the dialogue module, using statistics, an automaton and a
planner. A dialogue memory is constructed incrementally.Comment: Postscript file, compressed and uuencoded, 15 pages, to appear in
Proceedings of EACL-95, Dublin
Utilizing Statistical Dialogue Act Processing in Verbmobil
In this paper, we present a statistical approach for dialogue act processing
in the dialogue component of the speech-to-speech translation system \vm.
Statistics in dialogue processing is used to predict follow-up dialogue acts.
As an application example we show how it supports repair when unexpected
dialogue states occur.Comment: 6 pages; compressed and uuencoded postscript file; to appear in
ACL-9
Semantic and dialogue processing in the VERBMOBIL spoken dialogue translation system
In this paper we sketch the role of semantic and dialogue processing in the Verbmobil spoken dialogue translation system. A full demonstration system is currently under development although a "mini\u27; demonstration system has been implemented
Integrating Syntactic and Prosodic Information for the Efficient Detection of Empty Categories
We describe a number of experiments that demonstrate the usefulness of
prosodic information for a processing module which parses spoken utterances
with a feature-based grammar employing empty categories. We show that by
requiring certain prosodic properties from those positions in the input where
the presence of an empty category has to be hypothesized, a derivation can be
accomplished more efficiently. The approach has been implemented in the machine
translation project VERBMOBIL and results in a significant reduction of the
work-load for the parser.Comment: To appear in the Proceedings of Coling 1996, Copenhagen. 6 page
Some experiments in speech act prediction
In this paper, we present a statistical approach for speech act prediction in the dialogue component of the speech-to-speech translation system Verbmobil. The prediction algorithm is based on work known from language modelling and uses N-gram information computed from a training corpus. We demonstrate the performance of this method with 10 experiments. These experiments vary in two dimensions, namely whether the N-gram information is updated while processing, and whether deviations from the standard dialogue structure are processed. Six of the experiments use complete dialogues, while four process only the speech acts of one dialogue partner. It is shown that the predictions are best when using the update feature and deviations are not processed. Even the processing of incomplete dialogues then yields acceptable results. Another experiment shows that a training corpus size of about 40 dialogues is sufficient for the prediction task, and that the structure of the dialogues of the Verbmobil corpus we use differs remarkably with respect to the predictions
Prosodic processing and its use in Verbmobil
We present the prosody module of the VERBMOBlL speech-to-speech translation system, the world wide first complete system, which successfully uses prosodic information in the linguistic analysis. This is achieved by computing probabilities for clause boundaries, accentuation, and different types of sentence mood for each of the word hypotheses computed by the word recognizer. These probabilities guide the search of the linguistic analysis. Disambiguation is already achieved during the analysis and not by a prosodic verification of different linguistic hypotheses. So far, the most useful prosodic information is provided by clause boundaries. These are detected with a recognition rate of 94%. For the parsing of word hypotheses graphs, the use of clause boundary probabilities yields a speed-up of 92% and a 96% reduction of alternative readings
A multi-dimensional representation of context in a speech translation system : a practical approach
In this paper we show how the notion of context has been refined in order to fulfill the requirements posed by a natural language processing system. We describe the context model of the speech translation system Verbmobil which has been derived from constraints given by various system components. In Verbmobil context is stored in the dialogue memory which is incrementally constructed by the dialogue processing component. We describe our context model and give sample representations. We also relate our model to state of the art approaches in linguistics
Improving parsing of spontaneous speech with the help of prosodic boundaries
Parsing can be improved in automatic speech understanding if prosodic boundary marking is taken into account, because syntactic boundaries are often marked by prosodic means. Because large databases are needed for the training of statistical models for prosodic boundaries, we developed a labeling scheme for syntactic-prosodic boundaries within the German VERBMOBIL project (automatic speech-to-speech translation). We compare the results of classifiers (multi-layer perceptrons and language models) trained on these syntactic-prosodic boundary labels with classifiers trained on perceptual-prosodic and purely syntactic labels. Recognition rates of up to 96% were achieved. The turns that we need to parse consist of 20 words on the average and frequently contain sequences of partial sentence equivalents due to restarts, ellipsis, etc. For this material, the boundary scores computed by our classifiers can successfully be integrated into the syntactic parsing of word graphs; currently, they improve the parse time by 92% and reduce the number of parse trees by 96%. This is achieved by introducing a special Prosodic Syntactic Clause Boundary symbol (PSCB) into our grammar and guiding the search for the best word chain with the prosodic boundary scores
Plan recognition in verbmobil
Verbmobil, a speech to speech translation system, poses new and challenging tasks for a dialogue component. We present a part of the dialogue component of verbmobil: a robust plan recognizer that processes all of the over 200 dialogues of the verbmobil corpus. The recognizer currently handles unexpected sequences of input, and will in the future deal with multiple input, hypotheses, and incomplete input
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