Z.-I. Skordilis

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—In this paper, we examine three problems that rise in the modern, challenging area of far-field speech processing. The developed methods for each problem, namely (a) multi-channel speech enhancement, (b) voice activity detection, and (c) speech recognition, are potentially applicable to a distant speech recognition system for voice-enabled smart home(More)
The need for reliable, scalable and efficient diagnosis of Parkin-son's Disease (PD) is a major clinical need. Automating the diagnosis can lead to more accurate and objective predictions as well as provide insights regarding the nature of Parkinson's condition. This paper proposes a fully automated system to rate the severity (UPDRS-III scale) of PD from(More)
In this work, we investigate the efficacy of Micro Electro-Mechanical System (MEMS) microphones, a newly developed technology of very compact sensors, for multichannel speech enhancement. Experiments are conducted on real speech data collected using a MEMS microphone array. First, the effectiveness of the array geometry for noise suppression is explored,(More)
Automatically evaluating pronunciation quality of non-native speech has seen tremendous success in both research and commercial settings, with applications in L2 learning. In this paper, submitted for the INTERSPEECH 2015 Degree of Nativeness Sub-Challenge, this problem is posed under a challenging cross-corpora setting using speech data drawn from multiple(More)
The human tongue is an important organ for speech production. Its deformation and motion control the shape of the vocal tract significantly and thereby the acoustic properties of the speech signal produced. Thus, much effort in the speech research community has been directed towards its biomechanical modeling. A common assumption incorporated into many(More)
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