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Aphasic Speech Recognition Using a Mixture of Speech Intelligibility Experts.

, , and . INTERSPEECH, page 4986-4990. ISCA, (2020)

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Naturalistic Head Motion Generation from Speech., , , , and . ICASSP, page 1-5. IEEE, (2023)Aphasic Speech Recognition Using a Mixture of Speech Intelligibility Experts., , and . INTERSPEECH, page 4986-4990. ISCA, (2020)dMel: Speech Tokenization made Simple., , , , , and . CoRR, (2024)Using regional saliency for speech emotion recognition., and . ICASSP, page 2741-2745. IEEE, (2017)Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning., , and . ICMI, page 174-184. ACM, (2019)Robust Methods for the Automatic Quantification and Prediction of Affect in Spoken Interactions.. University of Michigan, USA, (2020)Identifying Mood Episodes Using Dialogue Features from Clinical Interviews., , , , and . INTERSPEECH, page 1926-1930. ISCA, (2019)Muse-ing on the Impact of Utterance Ordering on Crowdsourced Emotion Annotations., , , , , , and . ICASSP, page 7415-7419. IEEE, (2019)Improving End-of-Turn Detection in Spoken Dialogues by Detecting Speaker Intentions as a Secondary Task., , and . ICASSP, page 6159-6163. IEEE, (2018)Pooling acoustic and lexical features for the prediction of valence., , , and . ICMI, page 68-72. ACM, (2017)