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Enhancing In-the-Wild Speech Emotion Conversion with Resynthesis-based Duration Modeling
Navin Raj Prabhu, Danilo de Oliveira, Nale Lehmann-Willenbrock +1
Speech Emotion Conversion aims to modify the emotion expressed in input speech while preserving lexical content and speaker identity. Recently, generative modeling approaches have…
EMOCONV-DIFF: Diffusion-based Speech Emotion Conversion for Non-parallel and In-the-wild Data
Navin Raj Prabhu, Bunlong Lay, Simon Welker +2
Speech emotion conversion is the task of converting the expressed emotion of a spoken utterance to a target emotion while preserving the lexical content and speaker identity. While…
In-the-wild Speech Emotion Conversion Using Disentangled Self-Supervised Representations and Neural Vocoder-based Resynthesis
Navin Raj Prabhu, Nale Lehmann-Willenbrock, Timo Gerkmann
Speech emotion conversion aims to convert the expressed emotion of a spoken utterance to a target emotion while preserving the lexical information and the speaker's identity. In th…
Leveraging Semantic Information for Efficient Self-Supervised Emotion Recognition with Audio-Textual Distilled Models
Danilo de Oliveira, Navin Raj Prabhu, Timo Gerkmann
In large part due to their implicit semantic modeling, self-supervised learning (SSL) methods have significantly increased the performance of valence recognition in speech emotion…