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Bayesian and Gaussian Process Neural Networks for Large Vocabulary Continuous Speech Recognition.

, , , , , , , and . ICASSP, page 6555-6559. IEEE, (2019)

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Investigation of Data Augmentation Techniques for Disordered Speech Recognition., , , , , , and . CoRR, (2022)Generalized variable parameter HMMs based acoustic-to-articulatory inversion., , , and . INTERSPEECH, page 279-283. ISCA, (2015)Deep Neural Network Based Acoustic-to-Articulatory Inversion Using Phone Sequence Information., , and . INTERSPEECH, page 1497-1501. ISCA, (2016)Variational Auto-Encoder Based Variability Encoding for Dysarthric Speech Recognition., , , and . Interspeech, page 4808-4812. ISCA, (2021)Neural Architecture Search for LF-MMI Trained Time Delay Neural Networks., , , , , , and . ICASSP, page 6758-6762. IEEE, (2021)Adversarial Data Augmentation Using VAE-GAN for Disordered Speech Recognition., , , , , , , and . ICASSP, page 1-5. IEEE, (2023)Bayesian Learning for Deep Neural Network Adaptation., , , and . CoRR, (2020)Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognition., , , , , , , and . CoRR, (2022)Unsupervised Model-based speaker adaptation of end-to-end lattice-free MMI model for speech recognition., , , and . CoRR, (2022)Speaker Adaptation Using Spectro-Temporal Deep Features for Dysarthric and Elderly Speech Recognition., , , , , , , and . IEEE ACM Trans. Audio Speech Lang. Process., (2022)