http://hdl.handle.net/1842/3391 2013-05-20T05:41:49Z http://hdl.handle.net/1842/5206 Title: Infandango: Automated Grading for Student Programming Authors: Hull, Michael; Powell, Dan; Klein, Ewan Abstract: Infandango is an open source web-based system for automated grading of Java code submitted by students. Uploaded Java files are compiled and run against a set of unit tests on a central server, with results being stored in a database. Students gain near-instant feedback on the correctness of their code, and instructors are able to monitor the progress of students in the class. 2011-06-01T00:00:00Z http://hdl.handle.net/1842/4867 Title: The Romanian Speech Synthesis (RSS) corpus: building a high quality HMM-based speech synthesis system using a high sampling rate Authors: Stan, Adriana; Yamagishi, Junichi; King, Simon; Aylett, Matthew Abstract: This paper first introduces a newly-recorded high quality Romanian speech corpus designed for speech synthesis, called “RSS”, along with Romanian front-end text processing modules and HMM-based synthetic voices built from the corpus. All of these are now freely available for academic use in order to promote Romanian speech technology research. The RSS corpus comprises 3500 training sentences and 500 test sentences uttered by a female speaker and was recorded using multiple microphones at 96 kHz sampling frequency in a hemianechoic chamber. The details of the new Romanian text processor we have developed are also given. Using the database, we then revisit some basic configuration choices of speech synthesis, such as waveform sampling frequency and auditory frequency warping scale, with the aim of improving speaker similarity, which is an acknowledged weakness of current HMM-based speech synthesisers. As we demonstrate using perceptual tests, these configuration choices can make substantial differences to the quality of the synthetic speech. Contrary to common practice in automatic speech recognition, higher waveform sampling frequencies can offer enhanced feature extraction and improved speaker similarity for HMM-based speech synthesis. 2011-03-01T00:00:00Z http://hdl.handle.net/1842/4866 Title: Speaker similarity evaluation of foreign-accented speech synthesis using HMM-based speaker adaptation Authors: Wester, Mirjam; Karhila, Reima Abstract: This paper describes a speaker discrimination experiment in which native English listeners were presented with natural and synthetic speech stimuli in English and were asked to judge whether they thought the sentences were spoken by the same person or not. The natural speech consisted of recordings of Finnish speakers speaking English. The synthetic stimuli were created using adaptation data from the same Finnish speakers. Two average voice models were compared: one trained on Finnish-accented English and the other on American-accented English. The experiments illustrate that listeners perform well at speaker discrimination when the stimuli are both natural or both synthetic, but when the speech types are crossed performance drops significantly. We also found that the type of accent in the average voice model had no effect on the listeners' speaker discrimination performance. 2011-05-01T00:00:00Z http://hdl.handle.net/1842/4865 Title: Roles of the Average Voice in Speaker-adaptive HMM-based Speech Synthesis Authors: Yamagishi, Junichi; Watts, Oliver; King, Simon; Usabaev, Bela Abstract: In speaker-adaptive HMM-based speech synthesis, there are a few speakers whose synthetic speech sounds worse than that of other speakers, despite having the same amount of adaptation data from within the same corpus. This paper investigates these fluctuations in quality and found that as mel-cepstral distance from the average voice becomes larger, the MOS scores generally become worse. Although the negative correlation obtained is not strong enough, this helps us improve the training and adaptation strategies for average voice models. Furthermore we remark that this correlation is strongly linked to “vocal attractiveness.” 2010-01-01T00:00:00Z