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Found 6 papers, 0 papers with code
Exploring speech style spaces with language models: Emotional TTS without emotion labels
Many frameworks for emotional text-to-speech (E-TTS) rely on human-annotated emotion labels that are often inaccurate and difficult to obtain.
Converting Anyone's Voice: End-to-End Expressive Voice Conversion with a Conditional Diffusion Model
A major challenge of expressive VC lies in emotion prosody modeling.
Revealing Emotional Clusters in Speaker Embeddings: A Contrastive Learning Strategy for Speech Emotion Recognition
In order to leverage this information, we introduce a novel contrastive pretraining approach applied to emotion-unlabeled data for speech emotion recognition.
Disentanglement of Emotional Style and Speaker Identity for Expressive Voice Conversion
Expressive voice conversion performs identity conversion for emotional speakers by jointly converting speaker identity and emotional style.
Expressive Voice Conversion: A Joint Framework for Speaker Identity and Emotional Style Transfer
Traditional voice conversion(VC) has been focused on speaker identity conversion for speech with a neutral expression.
Spectrum and Prosody Conversion for Cross-lingual Voice Conversion with CycleGAN
It relies on non-parallel training data from two different languages, hence, is more challenging than mono-lingual voice conversion.
