An Application of SVM to Lost Packets Reconstruction in Voice-Enabled Services

Voice over IP (VoIP) is becoming very popular due to the huge range of services that can be implemented by integrating different media (voice, audio, data, etc.). Besides, voice-enabled interfaces for those services are being very actively researched. Nevertheless the impoverishment of voice quality due to packet losses severely affects the speech recognizers supporting those interfaces ([8]). In this paper, we have compared the usual lost packets reconstruction method with an SVM-based one that outperforms previous results

Robust ASR using Support Vector Machines

The improved theoretical properties of Support Vector Machines with respect to other machine learning alternatives due to their max-margin training paradigm have led us to suggest them as a good technique for robust speech recognition. However, important shortcomings have had to be circumvented, the most important being the normalisation of the time duration of different realisations of the acoustic speech units. In this paper, we have compared two approaches in noisy environments: first, a hybrid HMM–SVM solution where a fixed number of frames is selected by means of an HMM segmentation and second, a normalisation kernel called Dynamic Time Alignment Kernel (DTAK) first introduced in Shimodaira et al. [Shimodaira, H., Noma, K., Nakai, M., Sagayama, S., 2001. Support vector machine with dynamic time-alignment kernel for speech recognition. In: Proc. Eurospeech, Aalborg, Denmark, pp. 1841–1844] and based on DTW (Dynamic Time Warping). Special attention has been paid to the adaptation of both alternatives to noisy environments, comparing two types of parameterisations and performing suitable feature normalisation operations. The results show that the DTA Kernel provides important advantages over the baseline HMM system in medium to bad noise conditions, also outperforming the results of the hybrid system.Publicad

Agents in decentralised information ecosystems: the DIET approach

The complexity of the current global information infrastructure requires novel means of understanding and exploiting the dynamics of information. One means may be through the concept of an information ecosystem. An information ecosystem is analo gous to a natural ecosystem in which there are flo ws of materials and energy analo gous to information flow between many interacting individuals. This paper describes a multi-agent platform, DIET (Decentralised Information Ecosystem Technologies) that can be used to implement open, robust, adaptive and scalable ecosystem-inspired systems. We describe the design principles of the DIET software architecture, and present a simple example application based upon it. We go on to consider how the DIET system can be used to develop information brokering agents, and how these can contribute to the implementation of economic interactions between agents, as well as identifying some open questions relating to research in these areas. In this way we show the capacity of the DIET system to support applications using information agents.Future and Emerging Technologies arm of the IST Programme of the European Union, under the FET Proactive Initiative – Universal Information Ecosystems (FET, 1999), through project DIET (IST -1999-10088), BTexaCT Intelligent Systems Laboratory for stimulating discussion and comment

Auditory-inspired morphological processing of speech spectrograms: applications in automatic speech recognition and speech enhancement

New auditory-inspired speech processing methods are presented in this paper, combining spectral subtraction and two-dimensional non-linear filtering techniques originally conceived for image processing purposes. In particular, mathematical morphology operations, like erosion and dilation, are applied to noisy speech spectrograms using specifically designed structuring elements inspired in the masking properties of the human auditory system. This is effectively complemented with a pre-processing stage including the conventional spectral subtraction procedure and auditory filterbanks. These methods were tested in both speech enhancement and automatic speech recognition tasks. For the first, time-frequency anisotropic structuring elements over grey-scale spectrograms were found to provide a better perceptual quality than isotropic ones, revealing themselves as more appropriate—under a number of perceptual quality estimation measures and several signal-to-noise ratios on the Aurora database—for retaining the structure of speech while removing background noise. For the second, the combination of Spectral Subtraction and auditory-inspired Morphological Filtering was found to improve recognition rates in a noise-contaminated version of the Isolet database.This work has been partially supported by the Spanish Ministry of Science and Innovation CICYT Project No. TEC2008-06382/TEC.Publicad

Autophagy and Apoptosis Have a Role in the Survival or Death of Stallion Spermatozoa during Conservation in Refrigeration

Apoptosis has been recognized as a cause of sperm death during cryopreservation and a cause of infertility in humans, however there is no data on its role in sperm death during conservation in refrigeration; autophagy has not been described to date in mature sperm. We investigated the role of apoptosis and autophagy during cooled storage of stallion spermatozoa. Samples from seven stallions were split; half of the ejaculate was processed by single layer centrifugation, while the other half was extended unprocessed, and stored at 5°C for five days. During the time of storage, sperm motility (CASA, daily) and membrane integrity (flow cytometry, daily) were evaluated. Apoptosis was evaluated on days 1, 3 and 5 (active caspase 3, increase in membrane permeability, phosphatidylserine translocation and mitochondrial membrane potential) using flow cytometry. Furthermore, LC3B processing was investigated by western blotting at the beginning and at the end of the period of storage. The decrease in sperm quality over the period of storage was to a large extent due to apoptosis; single layer centrifugation selected non-apoptotic spermatozoa, but there were no differences in sperm motility between selected and unselected sperm. A high percentage of spermatozoa showed active caspase 3 upon ejaculation, and during the period of storage there was an increase of apoptotic spermatozoa but no changes in the percentage of live sperm, revealed by the SYBR-14/PI assay, were observed. LC3B was differentially processed in sperm after single layer centrifugation compared with native sperm. In processed sperm more LC3B-II was present than in non-processed samples; furthermore, in non-processed sperm there was an increase in LC3B-II after five days of cooled storage. These results indicate that apoptosis plays a major role in the sperm death during storage in refrigeration and that autophagy plays a role in the survival of spermatozoa representing a new pro-survival mechanism in spermatozoa not previously described

Segmentación de fonemas no supervisada basada en métodos kernel de máximo margen

Contains fulltext : 76402.pdf (author's version ) (Open Access)8 november 200

EXCHANGING USER PROFILES TO CONNECT PEERS IN DISTRIBUTED SYSTEMS

Abstract – In this paper we introduce a user profile exchange mechanism, called barter or trading without money, that does not make use of countable resources in a dynamic information retrieval environment. We consider a network of inter-connected users, who behave both as information consumers and producers, within a multi-agent system which operates in a peer-topeer fashion. Our aim is to get a fast and efficient information resource management (maximum profit) using a network topology as simple as possible (minimum cost), for a given set of user restrictions (limited memory and period of waiting)

Improved Variable Preselection List Length Estimation Using NNs

In very large vocabulary hypothesis-verification systems, the fine acoustic matcher is usually the most time consuming, so that the main concern is reducing the preselection list length as much as possible. Traditionally, these systems use a too high fixed preselection list length, increasing computational demands over the really needed. The idea we are proposing is estimating a different preselection list length for every utterance, so that we can lower the average computational effort needed for the recognition process. As we will show, it’s even possible that the resulting system outperforms the fixed length one in error rate, even when reducing computational cost. This paper presents a detailed study on a NN based approach to variable preselection list length estimation. The main achievement has been a relative decrease in error rate of up to 40%, while getting a relative decrease in average preselection list length of up to 31%. 1