Publication

On Modeling the Synergy Between Acoustic and Lexical Information for Pronunciation Lexicon Development

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Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Julian David Fritsch

Atypical aspects in speech concern speech that deviates from what is commonly considered normal or healthy. In this thesis, we propose novel methods for detection and analysis of these aspects, e.g. to monitor the temporary state of a speaker, diseases tha ...

EPFL2023

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 ...

Idiap2017

Acoustic data-driven grapheme-to-phoneme conversion in the probabilistic lexical modeling framework

Ramya Rasipuram, Marzieh Razavi

One of the primary steps in building automatic speech recognition (ASR) and text-to-speech systems is the development of a phonemic lexicon that provides a mapping between each word and its pronunciation as a sequence of phonemes. Phoneme lexicons can be d ...

2016

Automatic non-native accent assessment has potential benefits in language learning and speech technologies. The three fundamental challenges in automatic accent assessment are to characterize, model and assess individual variation in speech of the non-nati ...

2016

Problems and Procedures to Make Wordnet Data (Retro)Fit for a Multilingual Dictionary

Martin Benjamin

The data compiled through many Wordnet projects can be a rich source of seed information for a multilingual dictionary. However, the original Princeton WordNet was not intended as a dictionary per se, and spawning other languages from it introduces inheren ...

2016

Alexandru Ioan Cuza University of Iasi2016

Integrated 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 ...

2015

Acoustic and Lexical Resource Constrained ASR using Language-Independent Acoustic Model and Language-Dependent Probabilistic Lexical Model

Ramya Rasipuram

One of the key challenges involved in building statistical automatic speech recognition (ASR) systems is modeling the relationship between subword units or “lexical units” and acoustic feature observations. To model this relationship two types of resources ...

2015

Grapheme-based Automatic Speech Recognition using Probabilistic Lexical Modeling

Ramya Rasipuram

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 ...

EPFL2014

On Learning Grapheme-to-Phoneme Relationships through the Acoustic Speech Signal

Ramya Rasipuram

Automatic speech recognition (ASR) systems, through use of the phoneme as an intermediary unit representation, split the problem of modeling the relationship between the written form, i.e., the text and the acoustic speech signal into two disjoint processe ...

2014