ppxscal/embedding_network huggingface dataset:
A Simple But Effective Approach to Speaker Tracking in Broadcast News
Authors: Luis Javier Rodríguez, Mikel Peñagarikano, Germán Bordel
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

The automatic transcription of broadcast news and meetings involves the segmentation, identification and tracking of speaker turns during each session, which is known as speaker diarization. This paper presents a simple but effective approach to a slightly different task, called speaker tracking, also involving audio segmentation and speaker identification, but with a subset of known speakers, which allows to estimate speaker models and to perform identification on a segment-by-segment basis. The proposed algorithm segments the audio signal in a fully unsupervised way, by locating the most likely change points from an purely acoustic point of view. Then the available speaker data are used to estimate single-Gaussian acoustic models. Finally, speaker models are used to classify the audio segments by choosing the most likely speaker or, alternatively, the Other category, if none of the speakers is likely enough. Despite its simplicity, the proposed approach yielded the best performance in the speaker tracking challenge organized in November 2006 by the Spanish Network on Speech Technology.
IRQAS: information retrieval and question answering system based on a unified logical-linguistic model
Authors: Tengku M. T. Sembok
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Many existing search engines do not have an important capability, the capability to deduce an answer to a query based on information which reside in various parts of documents. The levels-of-processing theory proposes that there are many ways to process and code information and thus the knowledge representation used as surrogate to documents are qualitatively different. The capability of deduction is much depended on the knowledge representation framework used. We propose a unified logical-linguistic model as knowledge representation framework as a basis for indexing of documents as well as deduction capability to provide answers to queries. The approach applies semantic analysis in transforming and normalising information from natural language texts into a declarative knowledge based representation of first order predicate logic. Retrieval of relevant information can then be performed through plausible logical implication and answer to query is carried out using theorem proving technique. This paper elaborates on the model and how it is used in information retrieval and question answering system as one unified model.
Knowledge Services for Work-Integrated Learning
Authors: Stefanie N. Lindstaedt, Peter Scheir, Robert Lokaiczyk, Barbara Kump, Günter Beham, Viktoria Pammer
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

In order to support work-integrated learning scenarios task- and competency-aware knowledge services are needed. In this paper we introduce three key knowledge services of the APOSDLE system and illustrate how they interact. The context determination daemon observes user interactions and infers the current work task of the user. The user profile service uses the identified work tasks to determine the competences of the user. And finally, the associative retrieval service utilizes both the current work task and the inferred competences to identify relevant (learning) content. All of these knowledge services improve through user feedback.
Negation in Spatial Reasoning
Authors: Stefan Schleipen, Marco Ragni, Thomas Fangmeier
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

In recent years a lot of research has been done in order to determine factors of complexity in spatial relational reasoning, like the number of models, the wording of conclusion or the influence of relational complexity. But research so far focused on affirmative statements only, i. e. negated expressions have not yet been investigated. In spatial reasoning and in human machine interaction, however, negation plays a fundamental role. Central questions are: How are negated statements represented? What happens in multiple-model cases? Which effects have different reference frames? We conducted three experiments to show that humans (i) negate a relation by using the opposite relation, (ii) construct preferred mental models and use an economic principle, and (iii) have more difficulties in reasoning with negated relations. The goal is to extend our cognitive and computational model --- the SRM.
An Evolutionary Multi-objective Neural Network Optimizer with Bias-Based Pruning Heuristic
Authors: Prospero C. Naval,  Jr., John Paul Yusiong
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Neural network design aims for high classification accuracy and low network architecture complexity. It is also known that simultaneous optimization of both model accuracy and complexity improves generalization while avoiding overfitting on data. We describe a neural network training procedure that uses multi-objective optimization to evolve networks which are optimal both with respect to classification accuracy and architectural complexity. The NSGA-II algorithm is employed to evolve a population of neural networks that are minimal in both training error and a Minimum Description Length-based network complexity measure. We further propose a pruning rule based on the following heuristic: connections to or from a node may be severed if their weight values are smaller than the network's smallest bias. Experiments on benchmark datasets show that the proposed evolutionary multi-objective approach to neural network design employing the bias-based pruning heuristic yields networks that have far fewer connections without seriously compromising generalization performance when compared to other existing evolutionary optimization algorithms.
Topology Preserving Warping of Binary Images: Application to Atlas-Based Skull Segmentation
Authors: Sylvain Faisan, Nicolas Passat, Vincent Noblet, Renée Chabrier, Christophe Meyer
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Lots of works have been recently carried out in the field of non-rigid registration to ensure the estimation of one-to-one mappings. However, warping a binary image with such transformations may alter its discrete topological properties if common resampling strategies are considered. This paper proposes an original method for warping a binary image according to some continuous and bijective mapping, while preserving its discrete topological properties. Results obtained in the context of atlas-based segmentation highlight the interest of the approach. Indeed, the method has been successfully applied to the segmentation of skull structures from a database of 15 CT-scans, providing both geometrically and topologically satisfactory results.
The Evaluation of BP-ISP Strategy Alignment Degree with PSO-Based ANN
Authors: Lei Wen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

With the development of BP-ISP alignment research, how to evaluate the strategy alignment of BP-ISP become the key problem of this field. In this paper, a set of index system of evaluating the alignment of BP-ISP is established. Based on the index system, an integration algorithm with PSO and neural network is established to evaluate the alignment of BP-ISP. In order to verify the effectiveness of the method, a real case is given and BP neural network is also used to assess the same data. The experimental results show that integration algorithm with PSO and neural network is effective in the alignment evaluation of BP-ISP and achieves better performance than BP neural network.
Rules Extraction Based on Data Summarisation Approach Using DARA
Authors: Rayner Alfred
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

This paper helps the understanding and development of a data summarisation approach that summarises structured data stored in a non-target table that has many-to-one relations with the target table. In this paper, the feasibility of data summarisation techniques, borrowed from the Information Retrieval Theory, to summarise patterns obtained from data stored across multiple tables with one-to-many relations is demonstrated. The paper describes the Dynamic Aggregation of Relational Attributes (DARA) framework, which summarises data stored in non-target tables in order to facilitate data modelling efforts in a multi-relational setting. The application of the DARA algorithm involving structured data is presented in order to show the adaptability of this algorithm to real world problems. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Successive Abstractions of Hybrid Automata for Monotonic CTL Model Checking
Authors: R. Gentilini, K. Schneider, B. Mishra
Venue: Proceedings of the international symposium on Logical Foundations of Computer Science (2007)

Current symbolic techniques for the automated reasoning over undecidable hybrid automata, force one to choose between the refinement of either an overapproximation or an underapproximation of the set of reachable states. When the analysis of branching time temporal properties is considered, the literature has developed a number of abstractions techniques based on the simulation preorder, that allow the preservation of only true universally quantified formulæ.This paper suggests a way to surmount these difficulties by defining a succession of abstractions of hybrid automata, which not only (1) allow the detection and the refinement of both over- and under-approximated reachable sets symmetrically, but also (2) preserves the full set of branching time temporal properties (when interpreted on a dense time domain). Moreover, our approach imposes on the corresponding set of abstractions a desirable monotonicity property with respect to the set of model-checked formulaæ.
Data Hiding for Audio Based on Piecewise Linear Haar Transform
Authors: Diqun Yan, Rangding Wang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

In this paper, a data hiding algorithm based on PLHaar transform is proposed. The PLHaar transform maps an n-bit integer to another n-bit integer, and it guarantees no underflow/overflow to occur. Secret information is embedded into the LSB's of the PLHaar transform coefficients. Although the proposed algorithm has a slight decline in the quality of the stego audio compared with the algorithm based on Haar transform, it can recover the embedded secret information correctly without any additional operation.
Decision Making System: Agent Diagnosing Child Care Diseases
Authors: Vijay Kumar Mago, M. Syamala Devi, Ravinder Mehta
Venue: Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V (2007)

The use of Multi-agent systems (MAS) in healthcare domain has been widely recognized. But, due to uncertainty in medical domain, it is difficult to decide the appropriate agent with whom to collaborate in order to find the proper diagnosis for a given set of sign-symptoms. To overcome this problem, a Bayesian network (BN) based decision making framework is presented. The proposed methodology is applied to an Intelligent Pediatric Agent (IPA), a part of MAS for child care [1].
Finite volume and WENO scheme in one-dimensional vascular system modelling
Authors: N. Cavallini, V. Caleffi, V. Coscia
Venue: Computers Mathematics with Applications (2008)

A finite volume and WENO model is developed, validated and applied to a one-dimensional numerical investigation of the vascular system. Suitable balance laws are spatially integrated using a finite volume WENO approach. Time integration is performed using a five steps, fourth order accurate Runge-Kutta strong stability preserving scheme. A detailed investigation of different sets of reflecting and non-reflecting boundary conditions is performed to achieve a correct representation of limited portions of the vascular system. Moreover, special attention is devoted to the numerical discretisation of the source term. Finally, as an application of the whole model, the effect of an abdominal aorta aneurysm on the blood flow is evaluated.
A Multilingual Framework for Searching Definitions on Web Snippets
Authors: Alejandro Figueroa, Günter Neumann
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

This work presents Mdef-WQA, a system that searches for answers to definition questions in several languages on web snippets. For this purpose, Mdef-WQA biases the search engine in favour of some syntactic structures that often convey definitions. Once descriptive sentences are identified, Mdef-WQA clusters them by potential senses and presents the most relevant phrases of each potential sense to the user. The approach was assessed with TREC and CLEF data. As a result, Mdef-WQA was able to extract descriptive information for all definition questions in the TREC 2001 and 2003 data-sets.
Application-Specific Music Transcription for Tutoring
Authors: Ye Wang, Bingjun Zhang
Venue: IEEE MultiMedia (2008)

An application-specific, music-transcription approach uses a customized human&#x2013;computer interface to combine the strengths of humans and computers to enhance music transcription through instrument modeling and multimedia fusion.
Network Traffic Exploration Application: A Tool to Assess, Visualize, and Analyze Network Security Events
Authors: Grant Vandenberghe
Venue: Proceedings of the 5th international workshop on Visualization for Computer Security (2008)

Defence Research and Development Canada (DRDC) is developing a security event / packet analysis tool that is useful for analyzing a wide range of network attacks. The tool allows the security analyst to visually analyze a security event from a broad range of visual perspectives using a variety of detection algorithms. The tool is easy to extend and can be used to generate automated analysis scripts. The system architecture is presented and its capabilities are demonstrated through the analysis of several covert tunnels.
Investigating sighted users' browsing behaviour to assist web accessibility
Authors: Eleni Michailidou, Simon Harper, Sean Bechhofer
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

The rapid advancement of World Wide Web (Web) technology and constant need for attractive Websites produce pages that hinder visually impaired users. We assert that understanding how sighted users browse Web pages can provide important information that will enhance Web Accessibility, especially for visually impaired users. We present an eye tracking study where sighted users' browsing behaviour on nine Web pages was investigated to determine how the page's visual clutter is related to sighted users' browsing patterns. The results show that salient elements attract users' attention first, users spend more time on the main content of the page and users tend to fixate on the first three or four items on the menu lists. Common gaze patterns begin at the salient elements of the page, move to the main content, header, right column and left column of the page and finish at the footer area. We argue that the results should be used as the initial step for proposing guidelines that assist in designing and transforming Web pages for an easier and faster access for visually impaired users.
Cooperative User-Centric Digital Identity Management Framework for Public Web Portals
Authors: Sylvia Encheva, Sharil Tumin
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

This work focuses on control of users' access to public Web portals. A lightweight Web-based application framework is proposed for sharing users' data among federated organizations. A user receives an access-card after a subscription to a portal. The card is used as an identifier to the federated organizations' portal.
Local versus Global in Quasi-Conformal Mapping for Medical Imaging
Authors: Emil Saucan, Eli Appleboim, Efrat Barak-Shimron, Ronen Lev, Yehoshua Y. Zeevi
Venue: Journal of Mathematical Imaging and Vision (2008)

A method and algorithm of flattening folded surfaces, for two-dimensional representation and analysis of medical images, are presented. The method is based on an application to triangular meshes of classical results of Gehring and Väisälä regarding the existence of quasi-conformal and quasi-isometric mappings.The proposed algorithm is basically local and, therefore, suitable for extensively folded surfaces encountered in medical imaging. The theory and algorithm guarantee minimal distance, angle and area distortion. Yet, the algorithm is relatively simple, robust and computationally efficient, since it does not require computational derivatives. Both random-starting-point and curvature-based versions of the algorithm are presented.We demonstrate the algorithm using medical data obtained from real CT images of the colon and MRI scans of the human cortex. Further applications of the algorithm, for image processing in general are also considered. The globality of this algorithm is also studied, via extreme length methods for which we develop a technique of computing straightest geodesics on polyhedral surfaces.
Mechanism of Influenza A M2 Ion-Channel Inhibition: A Docking and QSAR Study
Authors: Alexander V. Gaiday, Igor A. Levandovskiy, Kendall G. Byler, Tatyana E. Shubina
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

Binding of blockers to the Influenza A ion-channel is studied using automated docking calculations. Our study suggests that studied cage compounds inhibit the M2 ion channel by binding to the His37 residue. The adamantane cage fits into a pocket formed by Trp41 residue, while the hydrogen bond is formed between hydrogen atom of ammonium nitrogen and the nitrogen of histidine residue. This finding is supported by experimental data and should help to obtain better understanding of the inhibition mechanism of the Influenza A M2 ion channel.
Approximating Graphs by Graphs and Functions (Abstract)
Authors: László Lovász
Venue: Proceedings of the 16th international symposium on Fundamentals of Computation Theory (2007)

In many areas of science huge networks (graphs) are central objects of study: the internet, the brain, various social networks, VLSI, statistical physics. To study these graphs, new paradigms are needed: What are meaningful questions to ask? When are two huge graphs "similar"? How to "scale down" these graphs without changing their fundamental structure and algorithmic properties? How to generate random examples with the desired properties? A reasonably complete answer can be given in the case when the huge graphs are dense (in the more difficult case of sparse graphs there are only partial results).
Fine Grain Distributed Implementation of a Dataflow Language with Provable Performances
Authors: Thierry Gautier, Jean-Louis Roch, Frédéric Wagner
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Efficient execution of multithreaded iterative numerical computations requires to carefully take into account data dependencies. This paper presents an original way to express and schedule general dataflow multithreaded computations. We propose a distributed dataflow stack implementation which efficiently supports work stealing and achieves provable performances on heterogeneous grids. It exhibits properties such as non-blocking local stack accesses and generation at runtime of optimized one-sided data communications.
Going Beyond the Problem Given: How Human Tutors Use Post-Solution Discussions to Support Transfer
Authors: Sandra Katz, David Allbritton, John Connelly
Venue: International Journal of Artificial Intelligence in Education (2003)

Two studies investigated the role and effectiveness of post-solution, reflective dialogues in physics tutorials. The first study investigated the instructional roles of post-solution discussions, their relationship to problem-solving discussions, and features that predict learning. Seven tutors individually guided 15 students as they worked on problems in the Andes physics tutoring system. Tutors adapted the post-solution discussions to students? ability levels and their performance on the current problem. Qualitative analysis of the transcripts revealed several roles of the post-solution dialogues - most prominently, explaining conceptual knowledge and integrating this knowledge with strategic, problem-solving knowledge. The number of post-solution discussions students had with their tutor, the number of discussions that abstracted from the current problem, and the number of tutor-initiated discussions predicted transfer, as measured by pre-test to post-test gain score on problems similar to those solved in Andes. Several tutorial strategies that are distributed between problem solving and post-solution reflection were identified. A framework for describing distributed plans for reflection is proposed based on these analyses. The second study investigated whether reflection questions such as those asked by the tutors in the first study lead to better conceptual understanding and problem-solving ability, as measured by overall gain scores and gain scores on conceptual and quantitative questions. It also examined whether human tutor-provided feedback on students?responses - with its often multi-exchange, dialectic character - is more effective than a single, canned explanation. Forty-six students solved problems in Andes in one of three conditions: with no reflection questions after problem solving, with reflection questions discussed with human tutors, or with the same reflection questions followed by canned feedback (without a human tutor). Students learned more with reflection questions and feedback than without, but the canned feedback and human tutored conditions did not differ significantly. Hence, overall, these studies support the practice of implementing post-solution reflective activities in intelligent tutoring systems, but call into question the need for natural-language processing techniques to support these activities.
Detection of Phoneme Boundaries Using Spiking Neurons
Authors: Gábor Gosztolya, László Tóth
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Automatic speech recognition (ASR) is an area where the task is to assign the correct phoneme or word sequence to an utterance. The idea behind the ASR segment-based approach is to treat one phoneme as a whole unit in every respect, in contrast with the frame-based approach where it is divided into equal-sized, smaller chunks. Doing this has many advantages, but also gives rise to some new problems. One of these is the detection of potential bounds between phones, which has an effect on both the recognition accuracy and the speed of the speech recognition system. In this paper we present three ways of boundary detection: first two simple algorithms are tested, then we will concentrate on our novel method which incorporates a spiking neuron. On examining the test results we find that the latter algorithm indeed proves successful: we were able to speed up the recognition process by 35.72% while also slightly improving the recognition performance.