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Multi-Modal Learning for Speech Emotion Recognition: An Analysis and Comparison of ASR Outputs with Ground Truth Transcription.

, , , and . INTERSPEECH, page 3302-3306. ISCA, (2019)

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Robust speech recognition using articulatory gestures in a Dynamic Bayesian Network framework., , and . ASRU, page 131-136. IEEE, (2011)Diversity of tongue shapes for the American English rhotic liquid., , , and . ICPhS, University of Glasgow, (2015)Knowledge-based parameters for HMM speech recognition., and . ICASSP, page 29-32. IEEE Computer Society, (1996)Semi-Supervised and Transfer Learning Approaches for Low Resource Sentiment Classification., , , and . ICASSP, page 5109-5113. IEEE, (2018)Smoothing Model Predictions Using Adversarial Training Procedures for Speech Based Emotion Recognition., , , and . ICASSP, page 4934-4938. IEEE, (2018)From acoustics to Vocal Tract time functions., , , , and . ICASSP, page 4497-4500. IEEE, (2009)An Empirical Analysis on the Vulnerabilities of End-to-End Speech Segregation Models., , , and . INTERSPEECH, page 5408-5412. ISCA, (2022)A semi-automatic approach for speaker mining of tapped telephone conversations., and . INTERSPEECH, page 2009-2012. ISCA, (2007)A new strategy of formant tracking based on dynamic programming., and . INTERSPEECH, page 55-58. ISCA, (2000)A Comparative Acoustic Study on Speech of Glossectomy Patients and Normal Subjects., , and . INTERSPEECH, page 517-520. ISCA, (2011)