Library and Information Science Commons^™

Mispronunciation Detection For Language Learning And Speech Recognition Adaptation, Zhenhao Ge

Open Access Dissertations

The areas of "mispronunciation detection" (or "accent detection" more specifically) within the speech recognition community are receiving increased attention now. Two application areas, namely language learning and speech recognition adaptation, are largely driving this research interest and are the focal points of this work.

There are a number of Computer Aided Language Learning (CALL) systems with Computer Aided Pronunciation Training (CAPT) techniques that have been developed. In this thesis, a new HMM-based text-dependent mispronunciation system is introduced using text Adaptive Frequency Cepstral Coefficients (AFCCs). It is shown that this system outperforms the conventional HMM method based on Mel Frequency Cepstral …

Overview: The Role Of Information Policy In Resolving Global Challenges, Sharon A. Weiner

Purdue Policy Research Institute (PPRI) Policy Briefs

Governments in many countries recognize the importance of knowledge-based societies whose citizens are adaptable and have the means to engage in continuous learning. Information societies can address global challenges far more readily than those that do not adopt its characteristics of ICTs (information and communication technologies) and connectivity; usable content; infrastructure and deliverability; and human intellectual capability.

A Justification For Semantic Training In Data Curation Frameworks Development, Xiaogang Ma, Benjamin D. Branch, Kristin Wegner

Libraries Faculty and Staff Presentations

In the complex data curation activities involving proper data access, data use optimization and data rescue, opportunities exist where underlying skills in semantics may play a crucial role in data curation professionals ranging from data scientists, to informaticists, to librarians. Here, We provide a conceptualization of semantics use in the education data curation framework (EDCF) (Fig. 1) [1] under development by Purdue University and endorsed by the GLOBE program [2] for further development and application. Our work shows that a comprehensive data science training includes both spatial and non-spatial data, where both categories are promoted by standard efforts of organizations …