Fabiola Martínez Licona

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Emotional speech recognition is a multidisciplinary research area that has received increasing attention over the last few years. The present paper considers the application of restricted Boltzmann machines (RBM) and deep belief networks (DBN) to the difficult task of automatic Spanish emotional speech recognition. The principal motivation lies in the(More)
We present a study on the quality of operation and the characteristics of the medical imaging equipment in three specialty hospitals of the Mexican Health System. Six month residencies were carried out in order to better understand the problems and internal functioning of the three imaging departments. The kinds of equipment, the types of equipment failures(More)
Biomedical Engineering (BME) has been taught in Mexico at the undergraduate level for over forty years. The rationale for the introduction of this profession was to help manage and maintain the growing technological infrastructure in the health care system during the seventies. Owing to this, it is not surprising that early versions of the BME curricula(More)
The synthetic voice produced from an HMM-based system is often reported as sounding muffled when it is compared to natural speech. There are several reasons for this effect: some precise and fine characteristics of the natural speech are removed, minimized or hidden in the modeling phase of the HMM system; the resulting speech-parameter trajectories become(More)
Spoken emotion recognition is a multidisciplinary research area that has received increasing attention over the last few years. In this paper, restricted Boltzmann machines and deep belief networks are used to classify emotions in speech. The motivation lies in the recent success reported using these alternative techniques in speech processing and speech(More)