Keywords:
- articulatory features
- Automatic accent assessment
- Automatic accent evaluation
- Automatic Speech Recognition
- automatic subword unit derivation
- dynamic programming
- grapheme
- Grapheme subword units
- grapheme subwords
- grapheme-based automatic speech recognition
- grapheme-to- phoneme conversion
- grapheme-to-phoneme conversion
- grapheme-to-phoneme converter
- Graphemes
- Hidden Markov Model
- KL-divergence
- KL-HMM
- Kullback-Leibler divergence
- Kullback-Leibler divergence based hidden Markov model
- Kullback–Leibler divergence based hidden Markov model
- letter-to-sound rules
- lexical model
- Lexical modeling
- Lexicon
- multi- layer perceptron
- multilayer perceptron
- multitask learning
- non-native speech
- non-native speech recognition
- objective measures
- phoneme
- phoneme subword units
- phoneme subwords
- phonemes
- phonetic representation
- Posterior features
- posterior probabilities
- probabilistic lexical modeling
- pronunciation generation
- pronunciation lexicon
- Scottish Gaelic
- Speech intelligibility
- text-to-speech synthesis
- under-resource speech recognition
- under-resourced languages
- under-resourced speech recognition
- unsupervised adaptation
- utterance verification
- zero-resourced speech recognition
Publications of Ramya Rasipuram sorted by title
A
| Acoustic and Lexical Resource Constrained ASR using Language-Independent Acoustic Model and Language-Dependent Probabilistic Lexical Model, and , Idiap-RR-02-2014 |
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| Acoustic and Lexical Resource Constrained ASR using Language-Independent Acoustic Model and Language-Dependent Probabilistic Lexical Model, and , in: Speech Communication, 68:23–40, 2015 |
[DOI] [URL] |
| Acoustic Data-Driven Grapheme-to-Phoneme Conversion in the Probabilistic Lexical Modeling Framework, , and , Idiap-RR-10-2015 |
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| Acoustic data-driven grapheme-to-phoneme conversion in the probabilistic lexical modeling framework, , and , in: Speech Communication, 80, 2016 |
[DOI] |
| Acoustic Data-driven Grapheme-to-Phoneme Conversion using KL-HMM, and , Idiap-RR-38-2011 |
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| Acoustic Data-driven Grapheme-to-Phoneme Conversion using KL-HMM, and , in: Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing, 2012 |
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| Articulatory Feature based Continuous Speech Recognition using Probabilistic Lexical Modeling, and , Idiap-RR-19-2014 |
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| Articulatory feature based continuous speech recognition using probabilistic lexical modeling, and , in: Computer Speech and Language, 36:233-259, 2016 |
[DOI] |
| Automatic Accentedness Evaluation of Non-Native Speech Using Phonetic and Sub-Phonetic Posterior Probabilities, , , and , Idiap-RR-12-2015 |
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| Automatic Accentedness Evaluation of Non-Native Speech Using Phonetic and Sub-Phonetic Posterior Probabilities, , , and , in: Proceedings of Interspeech, 2015 |
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C
| Combining Acoustic Data Driven G2P and Letter-to-Sound Rules for Under Resource Lexicon Generation, and , in: Proceedings of Interspeech, Portland, Oregon, 2012 |
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F
| Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition, , and , Idiap-RR-01-2012 |
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| Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition, , and , in: Proceedings of the IEEE workshop on Automatic Speech Recognition and Understanding, Hawaii, USA, pages 348-353, 2011 |
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G
| Grapheme and Multilingual Posterior Features For Under-Resource Speech Recognition: A Study on Scottish Gaelic, , and , Idiap-RR-34-2012 |
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| Grapheme and Multilingual Posterior Features for Under-Resourced Speech Recognition: A Study on Scottish Gaelic, , and , in: IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 |
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| Grapheme-based Automatic Speech Recognition using KL-HMM, , , and , in: Proceedings of Interspeech, 2011 |
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| Grapheme-based Automatic Speech Recognition using Probabilistic Lexical Modeling, , École polytechnique fédérale de Lausanne, 2014 |
[DOI] |
H
| HMM-based Non-native Accent Assessment using Posterior Features, , and , Idiap-RR-32-2015 |
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| HMM-based Non-native Accent Assessment using Posterior Features, , and , in: Proceedings of Interspeech, San Francisco, USA, 2016 |
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I
| Improving Articulatory Feature and Phoneme Recognition using Multitask Learning, and , in: Artificial Neural Networks and Machine Learning - ICANN 2011, pages 299-306, Springer Berlin / Heidelberg, 2011 |
[DOI] [URL] |
| Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach, and , Idiap-RR-14-2013 |
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| Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach, and , in: Proceedings of Interspeech, 2013 |
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| Integrated Pronunciation Learning for Automatic Speech Recognition Using Probabilistic Lexical Modeling, , and , in: International Conference on Acoustics, Speech and Signal Processing, South Brisbane, QLD, pages 5176-5180, 2015 |
[DOI] |
| Integrating Articulatory Features using Kullback-Leibler Divergence based Acoustic Model for Phoneme Recognition, and , Idiap-RR-02-2011 |
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| Integrating articulatory features using Kullback-Leibler divergence based acoustic model for phoneme recognition, and , in: Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, pages 5192 - 5195, 2011 |
[DOI] |
K
| KL-HMM and Probabilistic Lexical Modeling, and , Idiap-RR-04-2013 |
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M
| Multitask Learning to Improve Articulatory Feature Estimation and Phoneme Recognition, and , Idiap-RR-21-2011 |
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O
| Objective Intelligibility Assessment of Text-to-Speech Systems Through Utterance Verification, , , and , Idiap-RR-06-2015 |
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| Objective Intelligibility Assessment of Text-to-Speech Systems Through Utterance Verification, , , and , in: Proceedings of Interspeech, Dresden, Germany, pages 3501-3505, 2015 |
[URL] |
| On Learning Grapheme-to-Phoneme Relationships through the Acoustic Speech Signal, and , in: The Phonetician, 109–110:6-23, 2014 |
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| On Modeling Context-dependent Clustered States: Comparing HMM/GMM, Hybrid HMM/ANN and KL-HMM Approaches, , and , Idiap-RR-43-2013 |
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| On Modeling Context-Dependent Clustered States: Comparing HMM/GMM, Hybrid HMM/ANN and KL-HMM Approaches, , and , in: International Conference on Acoustics, Speech, and Signal Processing, Florence, IT, pages 7659 - 7663, IEEE, 2014 |
[DOI] |
| On the Application of Automatic Subword Unit Derivation and Pronunciation Generation for Under-Resourced Language ASR: A Study on Scottish Gaelic, , and , Idiap-RR-13-2015 |
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P
| Probabilistic Lexical Modeling and Grapheme-based Automatic Speech Recognition, and , Idiap-RR-15-2013 |
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| Probabilistic Lexical Modeling and Unsupervised Training for Zero-Resourced ASR, , and , in: Proceedings of the IEEE workshop on Automatic Speech Recognition and Understanding, 2013 |
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| Pronunciation Lexicon Development for Under-Resourced Languages Using Automatically Derived Subword Units: A Case Study on Scottish Gaelic, , and , in: 4th Biennial Workshop on Less-Resourced Languages, 2015 |
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T
| Towards Multiple Pronunciation Generation in Acoustic G2P Conversion Framework, , and , Idiap-RR-34-2015 |
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| Towards Weakly Supervised Acoustic Subword Unit Discovery and Lexicon Development Using Hidden Markov Models, , and , Idiap-RR-15-2017 |
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| Towards Weakly Supervised Acoustic Subword Unit Discovery and Lexicon Development Using Hidden Markov Models, , and , in: Speech Communication, 96:168-183, 2018 |
[DOI] |