Feature extraction for speech and music discrimination

Driven by the demand of information retrieval, video editing and human-computer interface, in this paper we propose a novel spectral feature for music and speech discrimination. This scheme attempts to simulate a biological model using the averaged cepstrum, where human perception tends to pick up the areas of large cepstral changes. The cepstrum data that is away from the mean value will be exponentially reduced in magnitude. We conduct experiments of music/speech discrimination by comparing the performance of the proposed feature with that of previously proposed features in classification. The dynamic time warping based classification verifies that the proposed feature has the best quality of music/speech classification in the test database

Connectionist Temporal Modeling for Weakly Supervised Action Labeling

We propose a weakly-supervised framework for action labeling in video, where only the order of occurring actions is required during training time. The key challenge is that the per-frame alignments between the input (video) and label (action) sequences are unknown during training. We address this by introducing the Extended Connectionist Temporal Classification (ECTC) framework to efficiently evaluate all possible alignments via dynamic programming and explicitly enforce their consistency with frame-to-frame visual similarities. This protects the model from distractions of visually inconsistent or degenerated alignments without the need of temporal supervision. We further extend our framework to the semi-supervised case when a few frames are sparsely annotated in a video. With less than 1% of labeled frames per video, our method is able to outperform existing semi-supervised approaches and achieve comparable performance to that of fully supervised approaches.Comment: To appear in ECCV 201

A design model for Open Distributed Processing systems

This paper proposes design concepts that allow the conception, understanding and development of complex technical structures for open distributed systems. The proposed concepts are related to, and partially motivated by, the present work on Open Distributed Processing (ODP). As opposed to the current ODP approach, the concepts are aimed at supporting a design trajectory with several, related abstraction levels. Simple examples are used to illustrate the proposed concepts

Agent Assistance: From Problem Solving to Music Teaching

We report on our research on agents that act and behave in a web learning environment. This research is part of a general approach to agents acting and behaving in virtual environments where they are involved in providing information, performing transactions, demonstrating products and, more generally, assisting users or visitors of the web environment in doing what they want or have been asked to do. While initially we hardly provided our agents with 'teaching knowledge', we now are in the process of making such knowledge explicit, especially in models that take into account that assisting and teaching takes place in a visualized and information-rich environment. Our main (embodied) tutor-agent is called Jacob; it knows about the Towers of Hanoi, a well-known problem that is offered to CS students to learn about recursion. Other agents we are working on assist a visitor in navigating in a virtual world or help the visitor in getting information. We are now designing a music teacher - using knowledge of software engineering and how to design multi-modal interactions, from previous projects

An Analytical Solution for Probabilistic Guarantees of Reservation Based Soft Real-Time Systems

We show a methodology for the computation of the probability of deadline miss for a periodic real-time task scheduled by a resource reservation algorithm. We propose a modelling technique for the system that reduces the computation of such a probability to that of the steady state probability of an infinite state Discrete Time Markov Chain with a periodic structure. This structure is exploited to develop an efficient numeric solution where different accuracy/computation time trade-offs can be obtained by operating on the granularity of the model. More importantly we offer a closed form conservative bound for the probability of a deadline miss. Our experiments reveal that the bound remains reasonably close to the experimental probability in one real-time application of practical interest. When this bound is used for the optimisation of the overall Quality of Service for a set of tasks sharing the CPU, it produces a good sub-optimal solution in a small amount of time.Comment: IEEE Transactions on Parallel and Distributed Systems, Volume:27, Issue: 3, March 201