Morphological processing of a dynamic compressive gammachirp filterbank for automatic speech recognition

Actas de: VII Jornadas en Tecnología del Habla and III Iberian SLTECH Workshop (IberSPEECH 2012). Madrid, 21-23 noviembre 2012.The Dynamic Compressive Gammachirp is presented for producing auditory-inspired feature extraction in Automatic Speech Recognition. The proposed acoustic features combine spectral subtraction and two-dimensional non-linear filtering technique most usually employed for image processing: morphological filtering. These features have been proven to be more robust to noisy speech than those based on simpler auditory filterbanks like the classical mel-scaled triangular filterbank, the Gammatone filterbank and the passive Gammachirp in a noisy Isolet database.This work has been partially supported by the Spanish Ministry of Science and Innovation CICYT Projects No. TEC2008-06382/TEC and No. TEC2011-26807.Publicad

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

Exercise benefits in cardiovascular disease : beyond attenuation of traditional risk factors

Despite strong scientific evidence supporting the benefits of regular exercise for the prevention and management of cardiovascular disease (CVD), physical inactivity is highly prevalent worldwide. In addition to merely changing well-known risk factors for systemic CVD, regular exercise can also improve cardiovascular health through non-traditional mechanisms. Understanding the pathways through which exercise influences different physiological systems is important and might yield new therapeutic strategies to target pathophysiological mechanisms in CVD. This Review includes a critical discussion of how regular exercise can have antiatherogenic effects in the vasculature, improve autonomic balance (thereby reducing the risk of malignant arrhythmias), and induce cardioprotection against ischaemia–reperfusion injury, independent of effects on traditional CVD risk factors. This Review also describes how exercise promotes a healthy anti-inflammatory milieu (largely through the release of muscle-derived myokines), stimulates myocardial regeneration, and ameliorates age-related loss of muscle mass and strength, a frequently overlooked non-traditional CVD risk factor. Finally, we discuss how the benefits of exercise might also occur via promotion of a healthy gut microbiota. We argue, therefore, that a holistic view of all body systems is necessary and useful when analysing the role of exercise in cardiovascular health