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Data driven articulatory synthesis with deep neural networks

  • Published:2016-03 Issue: Volume:36 Page:260-273
  • ISSN:0885-2308
  • Container-title:Computer Speech & Language
  • language:en
  • Short-container-title:Computer Speech & Language

Author:

Aryal Sandesh,Gutierrez-Osuna Ricardo

Publisher

Elsevier BV

Subject

Human-Computer Interaction,Theoretical Computer Science,Software

Reference52 articles.

1. Deep canonical correlation analysis;Andrew,2013

2. Multi-view CCA-based acoustic features for phonetic recognition across speakers and domains;Arora,2013

3. Articulatory inversion and synthesis: towards articulatory-based modification of speech;Aryal,2013

4. Accent conversion through cross-speaker articulatory synthesis;Aryal,2014

5. Investigation on dimensionality reduction of concatenated features with deep neural network for LVCSR systems;Bao,2012

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1. On The Performance of EMA-Synchronized Speech and Stand-alone Speech in Speech Recognition and Acoustic-to-Articulatory Inversion;Proceedings of the 2024 International Conference on Generative Artificial Intelligence and Information Security;2024-05-10

2. Evaluating Methods for Ground-Truth-Free Foreign Accent Conversion;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

3. Articulation GAN: Unsupervised Modeling of Articulatory Learning;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

4. Silent Speech Interface With Vocal Speaker Assistance Based on Convolution-Augmented Transformer;IEEE Transactions on Instrumentation and Measurement;2023

5. A deep learning approaches in text-to-speech system: a systematic review and recent research perspective;Multimedia Tools and Applications;2022-09-29
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