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Found 5 papers, 0 papers with code
On Feature Importance and Interpretability of Speaker Representations
Unsupervised speech disentanglement aims at separating fast varying from slowly varying components of a speech signal.
Investigating Speaker Embedding Disentanglement on Natural Read Speech
To quantify disentanglement, we identify acoustic features that are highly speaker-variant and can serve as proxies for the factors of variation underlying speech.
Investigation into Target Speaking Rate Adaptation for Voice Conversion
Disentangling speaker and content attributes of a speech signal into separate latent representations followed by decoding the content with an exchanged speaker representation is a popular approach for voice conversion, which can be trained with non-parallel and unlabeled speech data.
How to Address Smart Homes with a Social Robot? A Multi-modal Corpus of User Interactions with an Intelligent Environment
In order to explore intuitive verbal and non-verbal interfaces in smart environments we recorded user interactions with an intelligent apartment.
ALICO: a multimodal corpus for the study of active listening
The Active Listening Corpus (ALICO) is a multimodal database of spontaneous dyadic conversations with diverse speech and gestural annotations of both dialogue partners.
