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Related publications (19)
Towards Weakly Supervised Acoustic Subword Unit Discovery and Lexicon Development Using Hidden Markov Models
Ramya Rasipuram, Marzieh Razavi
Developing a phonetic lexicon for a language requires linguistic knowledge as well as human effort, which may not be available, particularly for under-resourced languages. An alternative to development of a phonetic lexicon is to automatically derive subwo ...
Idiap2017Integrated Pronunciation Learning for Automatic Speech Recognition Using Probabilistic Lexical Modeling
Ramya Rasipuram, Marzieh Razavi
Standard automatic speech recognition (ASR) systems use phoneme-based pronunciation lexicon prepared by linguistic experts. When the hand crafted pronunciations fail to cover the vocabulary of a new domain, a grapheme-to-phoneme (G2P) converter is used to ...
2015Graphene
We report a full study of graphene synthesis by CVD on Cu surface. Two CVD methods have been developed. The first is a static one, which yields monolayer of graphene at low pressure of methane in 3 minutes at 1000 C. The second one is an equimolar method w ...
EPFL2015Grapheme-based Automatic Speech Recognition using Probabilistic Lexical Modeling
Automatic speech recognition (ASR) systems incorporate expert knowledge of language or the linguistic expertise through the use of phone pronunciation lexicon (or dictionary) where each word is associated with a sequence of phones. The creation of phone pr ...
EPFL2014Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach
There is growing interest in using graphemes as subword units, especially in the context of the rapid development of hidden Markov model (HMM) based automatic speech recognition (ASR) system, as it eliminates the need to build a phoneme pronunciation lexic ...
Idiap2013