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نویسنده
چکیده
In this paper, we present the work done in language identification for two air traffic control speech recognizers, one for continuous speech and the other one for a command interface. The system is able to distinguish between Spanish and English. We will confirm the advantage of using PPRLM over PRLM. All previous studies show that PPRLM is the technique with the best performance despite of its drawbacks: more processing time and labeled data is needed. No work has been published regarding the optimum weights which should be given to the language models to optimize the performance of the language recognizer. This paper addresses this topic, providing three different approaches for weight selection in the language model score. We will also see that a trigram language model improves performance. The final results are very good even with very short segments of speech.
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This paper presents a model to predict the phrase commands of the Fujisaki Model for F0 contour for the Portuguese Language. Phrase commands location in text is governed by a set of weighted rules. The amplitude (Ap) and timing (T0) of the phrase commands are predicted in separate neural networks. The features for both neural networks are discussed. Finally a comparison between target and predi...
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Solutions proposed in bibliography for multiple user allocation on the sub-bands of an OFDM system, adopting multiple antennas, require highly computational effort and consider delay insensitive applications. Our approach tends to overcome all these limitations relaxing some hypothesis in order to give a feasible solution. The proposed algorithm can be applied to a real multiple antenna OFDM sy...
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Classification performance for emotional user states found in the few realistic, spontaneous databases available is as yet not very high. We present a database with emotional children’s speech in a human-robot scenario. Baseline classification performance for seven classes is 44.5%, for four classes 59.2%. We discuss possible strategies for tuning, e.g., using only prototypes (based on annotati...
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We report work on mapping the acoustic speech signal, parametrized using Mel Frequency Cepstral Analysis, onto electromagnetic articulography trajectories from the MOCHA database. We employ the machine learning technique of Support Vector Regression, contrasting previous works that applied Neural Networks to the same task. Our results are comparable to those older attempts, even though, due to ...
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Recent auditory physiological evidence points to a modulation frequency dimension in the auditory cortex. This dimension exists jointly with the tonotopic acoustic frequency dimension. Thus, audition can be considered as a relatively slowly-varying two-dimensional representation, the “modulation spectrum,” where the first dimension is the well-known acoustic frequency and the second dimension i...
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Sine-wave speech (SWS) is a three-tone replica of speech, conventionally created by matching each constituent sinusoid in amplitude and frequency with the corresponding vocal tract resonance (formant). We propose an alternative technique where we take a high-quality multicomponent sinusoidal representation and decimate this model so that there are only three components per frame. In contrast to...
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