Alexandre M. A. Maciel

Development of a Speech Recognizer with the Tecnovoz Database

This paper describes the development of a robust speech recognition using a database collected in the scope of the Tecnovoz project. The speech recognition system is speaker independent, robust to noise and operates in a small footprint embedded hardware platform. Some issues about the database, the training of the acoustic models, the noise suppression front-end and the recognizers confidence measure are addressed in the paper. Although the database was especially designed for specific small-vocabulary tasks, the best system performance was obtained using triphone models rather than whole-word models.

Discovering Level of Participation in MOOCs through Clusters Analysis

This paper presents an analysis using hierarchical grouping method (ward grouping) and the non-hierarchical grouping method (k-means) to analyze the participation levels in activities and interactions in a virtual forum. Data came from a MOOC and it was on grammatical rules of Brazilian Portuguese. About 5100 participants integrated the course. It lasted about three months and the activities developed by means of the Openredu learning platform. We analyzed data of collaboration, interaction, and discussions in forums, access data and activity on the Openredu. The results pointed to three distinct engagement strategies. Those categories oriented the proposition of an interface design guidelines for MOOC to conceive adaptive strategies that permit to increase engagement and favor an improved learning experience.

An investigation of students behavior in discussion forums using Educational Data Mining.

Discussion forums are an important feature in the Distance Education courses, supporting learning and facilitating interaction between students and teachers. This work aims to investigate behavioral aspects of students in virtual learning environments using Educational Data Mining. It is proposed to use the K-Means clustering technique as a way to identify students with common patterns of behavior based on their interactions in the forums. This work achieves good results from the application of clustering technique for this particular issue. Discussion Forums; Distance Education; Behavior Aspects; Educational Data Mining; Clustering. I. INTRODUCTION Demand for Distance Learning (DL) has shown growth rates increasing. The results of educational census conducted in Brazil between the years 2013 and 2014 show that the 309 institutions surveyed, there are a total of 4,044,315 students enrolled in distance learning courses. This number is expected to become even more significant in 2015, as 82% of these institutions enrollment will be even greater. These results guarantee the DL one leadership position among the types of education in Brazil (1).

Investigation of architecture for verification and recognition of speaker

The growing need to identify individuals becomes increasingly evident today, and biometrics are presented as the most safe and effective to perform this task. Among the various patterns that can be used in a biometric system, this work is dedicated to the study of the voice biometrics. Thus, a study of the area of voice processing and its applications were made and an architecture to systems of recognition and verification of a speaker was proposed. To that end, it was necessary to acquire a basic human voice to be built. The feature extractor MFCC (Mel Frequency cepstral coefficients) was used for the purpose of obtaining information that best representing each speaker. From the data obtained, was conducted a detailed study of the database (through statistical methods) and performance of Neural Networks MLP (Multilayer Perceptron) and SVM (Support Vectors Machines) were investigated to recognize the speakers. Besides In addition, the Vector Quantization also been applied to test speakers, showing satisfactory results.