Mircea Giurgiu

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Simple4All Tundra (version 1.0) is the first release of a standardised multilingual corpus designed for text-to-speech research with imperfect or found data. The corpus consists of approximately 60 hours of speech data from audiobooks in 14 languages, as well as utterance-level alignments obtained with a lightly-supervised process. Future versions of the(More)
This paper presents techniques for building text-to-speech front-ends in a way that avoids the need for language-specific expert knowledge, but instead relies on universal resources (such as the Unicode character database) and unsupervised learning from unannotated data to ease system development. The acquisition of expert language-specific knowledge and(More)
This paper reports on a multilingual investigation into the effects of different masker types on native and non-native perception in a VCV consonant recognition task. Native listeners outperformed 7 other language groups, but all groups showed a similar ranking of maskers. Strong first language (L1) interference was observed, both from the sound system and(More)
The use of shared projection neural nets of the sort used in language modelling is proposed as a way of sharing parameters between multiple text-to-speech system components. We experiment with pretraining the weights of such a shared projection on an auxiliary language modelling task and then apply the resulting word representations to the task of(More)
— This research assesses the ability of a Hidden Markov Model (HMM) based method to generate an accurate and reliable automatic phone-level transcriptions for a small vocabulary speech corpus. In particular, we are interested in a system that requires only orthographic transcription of the target corpus, and can be bootstrapped from models trained on an(More)
—This paper presents an novel authentication protocol that makes use of the server's public key and provides client's authenticity through its password without the need of a client side certificate or a second channel. Successful strategies for preventing man-in-the middle attacks are currently relying either on two channel/two factor authentication or(More)