Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
Objective Estimation Of Tracheoesophageal Speech Quality, Yousef S Ettomi Ali
Objective Estimation Of Tracheoesophageal Speech Quality, Yousef S Ettomi Ali
Electronic Thesis and Dissertation Repository
Speech quality estimation for pathological voices is becoming an increasingly important research topic. The assessment of the quality and the degree of severity of a disordered speech is important to the clinical treatment and rehabilitation of patients. In particular, patients who have undergone total laryngectomy (larynx removal) produce Tracheoesophageal (TE) speech. In this thesis, we study the problem of TE speech quality estimation using advanced signal processing approaches. Since it is not possible to have a reference (clean) signal corresponding to a given TE speech (disordered) signal, we investigate in particular the non-intrusive techniques (also called single-ended or blind approaches) …
Receptive Fields Optimization In Deep Learning For Enhanced Interpretability, Diversity, And Resource Efficiency., Babajide Odunitan Ayinde
Receptive Fields Optimization In Deep Learning For Enhanced Interpretability, Diversity, And Resource Efficiency., Babajide Odunitan Ayinde
Electronic Theses and Dissertations
In both supervised and unsupervised learning settings, deep neural networks (DNNs) are known to perform hierarchical and discriminative representation of data. They are capable of automatically extracting excellent hierarchy of features from raw data without the need for manual feature engineering. Over the past few years, the general trend has been that DNNs have grown deeper and larger, amounting to huge number of final parameters and highly nonlinear cascade of features, thus improving the flexibility and accuracy of resulting models. In order to account for the scale, diversity and the difficulty of data DNNs learn from, the architectural complexity and …