Smartphones provide an efficient means for the collection of speech data; however, the quality of the corpora created in this fashion is not predictable. We describe an approach that allows us to post-process and rank ...

Speech technologies have matured over the past few decades and have made significant impacts in a variety of fields, from assistive technologies to personal assistants. However, speech system development is a resource ...

We investigate the performance of conventional bandwidth estimators for non- parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of ...

Mismatches between application and training data greatly reduce the performance of automatic speech recognition (ASR) systems. However, collecting suitable amounts of in-domain and application-specific data for training ...

We describe the integration of several tools to enable the end-to-end development of an Automatic Speech Recognition system in a typical under-resourced language. Google App Engine is employed as the core environment for ...

This paper introduces a model of affect to improve prosody in text-to-speech synthesis. It operates on the discourse level of text to predict the underlying linguistic factors that contribute towards emotional appraisal, ...