2,357 research outputs found

    Automatic database acquisition software for ISDN PC cards and analogue boards

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    This paper describes an application for automatic speechdatabases acquisition (ADA) developed by the authors in the framework of the EC Telematics Project SpeechDat II. The software is able to work with standard inexpensive PC cards for ISDN lines, as well as Dialogic Boards for analogue telephone lines. Both program versions share a common file format and configuration. Other important characteristics of the recording software are its simple set-up, a fast and flexible configuration of the recording session, the real-time monitoring of calls and disk space, and its proven robustness.Peer ReviewedPostprint (published version

    Synthesis using speaker adaptation from speech recognition DB

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    This paper deals with the creation of multiple voices from a Hidden Markov Model based speech synthesis system (HTS). More than 150 Catalan synthetic voices were built using Hidden Markov Models (HMM) and speaker adaptation techniques. Training data for building a Speaker-Independent (SI) model were selected from both a general purpose speech synthesis database (FestCat;) and a database design ed for training Automatic Speech Recognition (ASR) systems (Catalan SpeeCon database). The SpeeCon database was also used to adapt the SI model to different speakers. Using an ASR designed database for TTS purposes provided many different amateur voices, with few minutes of recordings not performed in studio conditions. This paper shows how speaker adaptation techniques provide the right tools to generate multiple voices with very few adaptation data. A subjective evaluation was carried out to assess the intelligibility and naturalness of the generated voices as well as the similarity of the adapted voices to both the original speaker and the average voice from the SI model.Peer ReviewedPostprint (published version

    Fir system identification using a linear combination of cumulants

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    A general linear approach to identifying the parameters of a moving average (MA) model from the statistics of the output is developed. It is shown that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. This result is then used to obtain a new well-conditioned linear method to estimate the MA parameters of a nonGaussian process. The proposed approach does not require a previous estimation of the filter order. Simulation results show improvement in performance with respect to existing methods.Peer ReviewedPostprint (published version

    The strategic impact of META-NET on the regional, national and international level

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    This article provides an overview of the dissemination work carried out in META-NET from 2010 until early 2014; we describe its impact on the regional, national and international level, mainly with regard to politics and the situation of funding for LT topics. This paper documents the initiative’s work throughout Europe in order to boost progress and innovation in our field.Postprint (published version

    Monolingual and bilingual spanish-catalan speech recognizers developed from SpeechDat databases

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    Under the SpeechDat specifications, the Spanish member of SpeechDat consortium has recorded a Catalan database that includes one thousand speakers. This communication describes some experimental work that has been carried out using both the Spanish and the Catalan speech material. A speech recognition system has been trained for the Spanish language using a selection of the phonetically balanced utterances from the 4500 SpeechDat training sessions. Utterances with mispronounced or incomplete words and with intermittent noise were discarded. A set of 26 allophones was selected to account for the Spanish sounds and clustered demiphones have been used as context dependent sub-lexical units. Following the same methodology, a recognition system was trained from the Catalan SpeechDat database. Catalan sounds were described with 32 allophones. Additionally, a bilingual recognition system was built for both the Spanish and Catalan languages. By means of clustering techniques, the suitable set of allophones to cover simultaneously both languages was determined. Thus, 33 allophones were selected. The training material was built by the whole Catalan training material and the Spanish material coming from the Eastern region of Spain (the region where Catalan is spoken). The performance of the Spanish, Catalan and bilingual systems were assessed under the same framework. The Spanish system exhibits a significantly better performance than the rest of systems due to its better training. The bilingual system provides an equivalent performance to that afforded by both language specific systems trained with the Eastern Spanish material or the Catalan SpeechDat corpus.Peer ReviewedPostprint (published version

    New hos-based parameter estimation methods for speech recognition in noisy environments

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    The problem of recognition in noisy environments is addressed. Often, a recognition system is used in a noisy environment and there is no possibility of training it with noisy samples. Classical speech analysis techniques are based on second-order statistics and their performance dramatically decreases when noise is present in the signal under analysis. New methods based on higher order statistics (HOS) are applied in a recognition system and compared against the autocorrelation method. Cumulant-based methods show better performance than autocorrelation-based methods for low SNRPeer ReviewedPostprint (published version

    Wetland restoration and nitrate reduction: the example of the periurban wetland of Vitoria-Gasteiz (Basque Country, North Spain)

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    Changes in land use and agricultural intensification caused wetlands on the quaternary aquifer of Vitoria-Gasteiz (Basque Country) to disappear some years ago and nitrate concentration in groundwaters increased very quickly. The Basque Government recently declared the East Sector of this aquifer a Vulnerable Zone according to the 91/676/CEE European Directive. Recently, the wetlands have been restored through the closure of the main drainage ditches, the consequent elevation of the water table and the abondonment of agricultural practices near the wetlands. This is the case of the Zurbano wetland. Restoration has allowed the recovery of its biogeochemical function, which has reduced nitrate concentrations in waters. Nitrate concentrations which exceed 50 mg l–1 in groundwaters entering into the wetland are less than 10 mg l–1 at the outlet. Conditions in the wetland are conducive to the loss of nitrates: organic matter rich wetted soils, clay presence allowing a local semiconfined flow and very low hydraulic gradient. Water quality monitoring at several points around the wetland showed the processes involved in nitrate loss, although some aspects still remain unresolved. However, during storm events, the wetland effectively reduces the nitrate concentration entering the Alegria River, the most important river on the quaternary aquifer

    Explicit exactly energy-conserving methods for Hamiltonian systems

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    For Hamiltonian systems, simulation algorithms that exactly conserve numerical energy or pseudo-energy have seen extensive investigation. Most available methods either require the iterative solution of nonlinear algebraic equations at each time step, or are explicit, but where the exact conservation property depends on the exact evaluation of an integral in continuous time. Under further restrictions, namely that the potential energy contribution to the Hamiltonian is non-negative, newer techniques based on invariant energy quadratisation allow for exact numerical energy conservation and yield linearly implicit updates, requiring only the solution of a linear system at each time step. In this article, it is shown that, for a general class of Hamiltonian systems, and under the non-negativity condition on potential energy, it is possible to arrive at a fully explicit method that exactly conserves numerical energy. Furthermore, such methods are unconditionally stable, and are of comparable computational cost to the very simplest integration methods (such as Störmer-Verlet). A variant of this scheme leading to a conditionally-stable method is also presented, and follows from a splitting of the potential energy. Various numerical results are presented, in the case of the classic test problem of Fermi, Pasta and Ulam and for nonlinear systems of partial differential equations, including those describing high amplitude vibration of strings and plates
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