A spiking neural network for real-time Spanish vowel phonemes recognition

This paper explores neuromorphic approach capabilities applied to real-time speech processing. A spiking recognition neural network composed of three types of neurons is proposed. These neurons are based on an integrative and fire model and are capable of recognizing auditory frequency patterns, such as vowel phonemes; words are recognized as sequences of vowel phonemes. For demonstrating real-time operation, a complete spiking recognition neural network has been described in VHDL for detecting certain Spanish words, and it has been tested in a FPGA platform. This is a stand-alone and fully hardware system that allows to embed it in a mobile system. To stimulate the network, a spiking digital-filter-based cochlea has been implemented in VHDL. In the implementation, an Address Event Representation (AER) is used for transmitting information between neurons.Ministerio de Economía y Competitividad TEC2012-37868-C04-02/0

Bot and gender detection of twitter accounts using distortion and LSA notebook for PAN at CLEF 2019

In this work, we present our approach for the Author Profiling task of PAN 2019. The task is divided into two sub-problems, bot, and gender detection, for two different languages: English and Spanish. For each instance of the problem and each language, we address the problem differently. We use an ensemble architecture to solve the Bot Detection for accounts that write in English and a single SVM for those who write in Spanish. For the Gender detection we use a single SVM architecture for both the languages, but we pre-process the tweets in a different way. Our final models achieve accuracy over the 90% in the bot detection task, while for the gender detection, of 84.17% and 77.61% respectively for the English and Spanish languages

Urban gaming simulation for enhancing disaster resilience: a social learning tool for modern disaster risk management

An emergence of the disaster resilience concept broadens the idea of urban risk management and, at the same time, enhances a theoretical aspect in a way in which we can develop our cities without making it more vulnerable to natural disasters. Nevertheless, this theoretical plausibility is hardly translated into a practical implication for urban planning, as the concept of resilience remain limited to some scholars’ debate. One of substantial factors that limit the understanding of people about disaster risk an resilience is a lack of risk awareness and risk preparedness, which can be solved by restructuring social learning process that enable a process of mutual learning between experts and the public. This study, therefore, focuses on providing insights into the difficulties of disaster risk communication we face, and how gaming simulation can be taken as a communication technique in enhancing social learning, which is regarded as a fundamental step of disaster risk management prior the mitigation process takes place. The study argues that the gaming simulation can facilitate planners in acquiring risk information from the community, conceiving the multitude of complex urban physical and socio-economic components, and conceptualizing innovative solutions to cope with disaster risks mutually with the public