This article analyzes the problem of modeling and compensation of friction at velocities close to zero. A new model, linear in parameters, which captures the downward bends at low velocity is used to adoptively compensate for friction. The need for this type of model is mainly motivated by instability phenomena that can be caused by overcompensation when simple models (such as Coulomb friction models) are used as a basis for the friction compensation. This model, in combination with an adaptive computed torque method, was tested experimentally in a robot manipulator.
This paper explores whether adding Discourse Relation (DR) features improves the naturalness of neural statistical parametric speech synthesis (SPSS) in English. We hypothesize firstin the light of several previous studies-that DRs have a dedicated prosodic encoding. Secondly, we hypothesize that encoding DRs in a speech synthesizer's input will improve the naturalness of its output. In order to test our hypotheses, we prepare a dataset of DR-annotated transcriptions of audiobooks in English. We then perform an acoustic analysis of the corpus which supports our first hypothesis that DRs are acoustically encoded in speech prosody. The analysis reveals significant correlation between specific DR categories and acoustic features, such as F0 and intensity. Then, we use the corpus to train a neural SPSS system in two configurations: a baseline configuration making use only of conventional linguistic features, and an experimental one where these are supplemented with DRs. Augmenting the inputs with DR features improves objective acoustic scores on a test set and leads to significant preference by listeners in a forced choice AB test for naturalness.
The paper analyzes the problem of modelling and compensation of friction at velocities close to zero. A new model, linear in parameters, which captures the downward bends at low velocity is used to adaptively compensate for friction. The need for this type of models is mainly motivated by instability phenomena that can be caused by overcompensation when simple models (such as Coulomb friction models) are used as a basis for the friction compensation. This model, in combination with an adaptive computed torque method were tested experimentally in the last link of a robot manipulator.
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