Automatic localization and diagnosis of pronunciation errors for second-language learners of English

An automatic system for detection of pronunciation errors by adult learners of English is embedded in a language–learning package. Four main features are: (1) a recognizer robust to non–native speech; (2) localization of phone– and word–level errors; (3) diagnosis of what sorts of phone–level errors took place; and (4) a lexical–stress detector. These tools together allow robust, consistent, and specific feedback on pronunciation errors, unlike many previous systems that provide feedbaconly at a more general level. The diagnosis technique searches for errors expected based on the student’s mother tongue and uses a separate bias for each error in order to maintain a particular desired global false alarm rate. Results are presented here for non–native recognition on tasks of differing complexity and for diagnosis, based on a data set of artificial errors, showing that this method can detect many contrasts with a high hit rate and a low false alarm rate

Social Cryptocurrencies: blockchain adoption by social finance organizations

This paper examines relevant dimensions to understand social cryptocurrencies, an emergent and promising phenomenon that pursues solidarity finance principles, such as financial inclusion and local economy development. In this paper we present a researc