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Leveraging Acoustic Cues and Paralinguistic Embeddings to Detect Expression from Voice.

, , , , , , , , and . INTERSPEECH, page 1651-1655. ISCA, (2019)

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Typicality and emotion in the voice of children with autism spectrum condition: evidence across three languages., , , , , , and . INTERSPEECH, page 115-119. ISCA, (2015)Improving Recognition of Speaker States and Traits by Cumulative Evidence: Intoxication, Sleepiness, Age and Gender., , and . INTERSPEECH, page 1159-1162. ISCA, (2012)The INTERSPEECH 2014 computational paralinguistics challenge: cognitive & physical load., , , , , , , and . INTERSPEECH, page 427-431. ISCA, (2014)Introducing the Weighted Trustability Evaluator for Crowdsourcing Exemplified by Speaker Likability Classification., , and . LREC, European Language Resources Association (ELRA), (2016)Detecting Emotion Primitives from Speech and Their Use in Discerning Categorical Emotions., , , , , , , and . ICASSP, page 7164-7168. IEEE, (2020)The state of play of ASC-Inclusion: An Integrated Internet-Based Environment for Social Inclusion of Children with Autism Spectrum Conditions., , , , , , and . CoRR, (2014)Real-time robust recognition of speakers' emotions and characteristics on mobile platforms., , , , and . ACII, page 778-780. IEEE Computer Society, (2015)Speech, Emotion, Age, Language, Task, and Typicality: Trying to Disentangle Performance and Feature Relevance., , , , , and . SocialCom/PASSAT, page 961-968. IEEE Computer Society, (2012)Generating Multilingual Voices Using Speaker Space Translation Based on Bilingual Speaker Data., , and . ICASSP, page 7624-7628. IEEE, (2020)Affective and behavioural computing: Lessons learnt from the First Computational Paralinguistics Challenge., , , , , , , , , and 2 other author(s). Comput. Speech Lang., (2019)