| 1. |
- Alshawi, Hiyan, et al.
(author)
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Bilingual conversation interpreter : a prototype interactive message translator. Final report
- 1991. - 1
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Reports (other academic/artistic)abstract
- This document is the final report for a research project aimed at producing a prototype system for on-line translation of typed dialogues between speakers of different natural languages. The work was carried out jointly by SICS and SRI Cambridge. The resulting prototype system (called Billingual Conversation Interpreter, or BCI) translates between english and Swedish in both directions.The Major components of the BCI are two copies of the SRI Core Language Engine, equipped with English and Swedish grammars respectively. These are linked by the transfer and disambiguation components. Translation takes place by analyzing the source-language sentence into Quasi Logical Form ( QLF), a linguistically motivated logical representation, transferring this into a target-language QLF, and generating a target-language sentence. When ambiguities occur that cannot be resolved automatically, they are clarified by Querying the appropriate user. The clarification dialogue presupposes no knowledge of either linguistics or the other language. The prototype system has a broad grammatical coverage, a initial vocabulary of about 1000 words together with vocabulary expansion tools, and a set of English-Swedish transfer rules. The formalism developed for coding this linguistic information make it relatively easy to extend the system. We believe that the project was successful in demonstrating the feasibility of using these techniques for interactive translation applications, and provides a sound basis for development of a large scale message translator system with potential for commercial exploitation.The main sections of this report are the following: * A non-technical introduction, summarizing the BCI's design , and containing a sample session. * An overview of the Swedish version of the CLE. * A detailed discussion of the theory and practice of QLF transfer. * A description of the interactive disambiguation method. * Suggestions for possible follow-on projects aimed in the direction of practically usable commercial systems.
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| 2. |
- Alshawi, Hiyan, et al.
(author)
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Transfer through quasi logical form - A new approach to machine translation
- 1991. - 1
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Reports (other academic/artistic)abstract
- This Document is an introduction to a research project aimed at producing a prototype system for on-line translation of typed dialogues between speakers of different natural languages. The work was carried out jointly by SICS and SRI Cambridge. The resulting prototype system (called Billingual Conversation Interpreter, or BCI) translates between English and Swedish in both Directions. The major components of the BCI are two copies of the SRI Core Language Engine, equipped with English and Swedish grammars respectively. These are linked by the transfer and disambiguation components. Translation takes place by analyzing the source-language sentence into Quasi Logical Form (QLF), a linguistically motivated logical representation, transferring this onto a target-language QLF, and generating a target-language sentence. We believe that the project was successful in demonstrating the feasibility of using these techniques for interactive translation applications, and provides a sound basis for development of a large scale message translator system. The final section of the paper points to several possible follow-on projects aimed in the direction of practically usable commercial systems.
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| 3. |
- Asker, Lars, et al.
(author)
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Classifying Amharic Webnews
- 2009
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In: Information retrieval (Boston). - : Springer Science and Business Media LLC. - 1386-4564 .- 1573-7659. ; 12:3, s. 416-435
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Journal article (peer-reviewed)abstract
- We present work aimed at compiling an Amharic corpus from the Web and automatically categorizing the texts. Amharic is the second most spoken Semitic language in the World (after Arabic) and used for countrywide communication in Ethiopia. It is highly inflectional and quite dialectally diversified. We discuss the issues of compiling and annotating a corpus of Amharic news articles from the Web. This corpus was then used in three sets of text classification experiments. Working with a less-researched language highlights a number of practical issues that might otherwise receive less attention or go unnoticed. The purpose of the experiments has not primarily been to develop a cutting-edge text classification system for Amharic, but rather to put the spotlight on some of these issues. The first two sets of experiments investigated the use of Self-Organizing Maps (SOMs) for document classification. Testing on small datasets, we first looked at classifying unseen data into 10 predefined categories of news items, and then at clustering it around query content, when taking 16 queries as class labels. The second set of experiments investigated the effect of operations such as stemming and part-of-speech tagging on text classification performance. We compared three representations while constructing classification models based on bagging of decision trees for the 10 predefined news categories. The best accuracy was achieved using the full text as representation. A representation using only the nouns performed almost equally well, confirming the assumption that most of the information required for distinguishing between various categories actually is contained in the nouns, while stemming did not have much effect on the performance of the classifier.
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| 4. |
- Benyon, David, et al.
(author)
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How Was Your Day? Evaluating a Conversational Companion
- 2013
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In: IEEE Transactions on Affective Computing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1949-3045. ; 4:3, s. 299-311
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Journal article (peer-reviewed)abstract
- The How Was Your Day(HWYD) companion is an embodied conversational agent that can discuss work-related issues, entering free-form dialogues while discussing issues surrounding a typical work day. The open-ended nature of these interactions requires new models of evaluation. Here, we describe a paradigm and methodology for evaluating the main aspects of such functionality in conjunction with overall system behavior, with respect to three parameters: functional ability (i.e., does it do the rightthing conversationally), content (i.e., does it respond appropriately to the semantic context), and emotional behavior (i.e., given the emotional input from the user, does it respond in an emotionally appropriate way). We demonstrate the functionality of our evaluation paradigm as a method for both grading current system performance, and targeting areas for particular performance review. We show correlation between, for example, automatic speech recognition performance and overall system performance (as is expected in systems of this type), but beyond this, we show where individual utterances or responses, indicated as positive or negative, characterize system performance, and demonstrate how our combination evaluation approach highlights issues (both positive and negative) in the companion system's interaction behavior.
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| 5. |
- Bullock, Adrian, et al.
(author)
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SenToy and FantasyA: evaluating affective gaming
- 2003. - 1
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Conference paper (peer-reviewed)abstract
- Gaming is a highly relevant application area for Intelligent Agents and Human Computer Interaction (HCI). Computer games bring us a full set of new gaming experiences where synthetic characters take on the main role.Using affective input in the interaction with a game and in particular with a character is a recent and fairly unexplored dimension. This video presents a study of a tangible interaction device for affective input and its use in a role-playing game where emotions are part of the game logic.
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| 6. |
- Cheadle, Maria, et al.
(author)
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Multi-session group scenarios for speech interface design
- 2003
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In: Human-Computer Interaction. - Mahwah, New Jersey : Lawrence Erlbaum Associates. - 0805849319 ; , s. 676-680
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Book chapter (peer-reviewed)abstract
- When developing adaptive speech-based multilingual interaction systems, we need representative data on the user's behaviour. In this paper we focus on a data collection method pertaining to adaptation in the user's interaction with the system. We describe a multi-session group scenario for Wizard of Oz studies with two novel features: firstly, instead of doing solo sessions with a static mailbox, our test users communicated with each other in a group of six, and secondly, the communication took place over several sessions in a period of five to eight days. The paper discusses our data collection studies using the method, concentrating on the usefulness of the method in terms of naturalness of the interaction and long-term developments.
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| 7. |
- Cheadle, Maria, et al.
(author)
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Robust semantic analysis for adaptive speech interfaces
- 2003
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In: Universal Access in HCI. - Mahwah, New Jersey : Lawrence Erlbaum Associates. - 0805849335 ; , s. 685-689
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Book chapter (peer-reviewed)abstract
- 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.
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| 8. |
- Eineborg, Martin, et al.
(author)
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Neural Networks for Wordform Recognition
- 1994. - 1
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Reports (other academic/artistic)abstract
- The paper outlines a method for automatic lexical acquisition using three-layered back-propagation networks. Several experiments have been carried out where the performance of different network architectures have been compared to each other on two tasks: overall part-of-speech (noun, adjective or verb) classification and classification by a set of 13 possible output categories. The best results for the simple task were obtained by networks consisting of 204-212 input neurons and 40 hidden-layer neurons, reaching a classification rate of 93.6%. The best result for the more complex task was 96.4%, which was achieved by a net with 423 input neurons and 80 hidden-layer neurons. These results are rather promising and the paper compares them to the performance reported by rule-based and purely statistical methods; a comparison that shows the neural network completely compatible with the statistical approach. The rule-based method is, however, still better, even though it should noted that the task that the rule-based system performs is somewhat different from that of the neural net.
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| 9. |
- Ekern, Erlend, et al.
(author)
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Interactive, Efficient and Creative Image Generation Using Compositional Pattern-Producing Networks
- 2021
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In: Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2021. Lecture Notes in Computer Science, vol 12693.. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783030729134 ; , s. 131-146
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Conference paper (peer-reviewed)abstract
- In contrast to most recent models that generate an entire image at once, the paper introduces a new architecture for generating images one pixel at a time using a Compositional Pattern-Producing Network (CPPN) as the generator part in a Generative Adversarial Network (GAN), allowing for effective generation of visually interesting images with artistic value, at arbitrary resolutions independent of the dimensions of the training data. The architecture, as well as accompanying (hyper-) parameters, for training CPPNs using recent GAN stabilisation techniques is shown to generalise well across many standard datasets. Rather than relying on just a latent noise vector (entangling various features with each other), mutual information maximisation is utilised to get disentangled representations, removing the requirement to use labelled data and giving the user control over the generated images. A web application for interacting with pre-trained models was also created, unique in the offered level of interactivity with an image-generating GAN.
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| 10. |
- Eyassu, Samuel, et al.
(author)
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Classifying Amharic News Text Using Self-Organizing Maps
- 2005. - 1
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Conference paper (peer-reviewed)abstract
- The paper addresses using artificial neural networks for classification of Amharic news items. Amharic is the language for countrywide communication in Ethiopia and has its own writing system containing extensive systematic redundancy. It is quite dialectally diversified and probably representative of the languages of a continent that so far has received little attention within the language processing field. The experiments investigated document clustering around user queries using Self-Organizing Maps, an unsupervised learning neural network strategy. The best ANN model showed a precision of 60.0% when trying to cluster unseen data, and a 69.5% precision when trying to classify it.
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