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Defining and Measuring Disentanglement for non-Independent Factors of Variation
In this paper we give a definition of disentanglement based on information theory that is also valid when the factors of variation are not independent.
Predefined Prototypes for Intra-Class Separation and Disentanglement
Prototypical Learning is based on the idea that there is a point (which we call prototype) around which the embeddings of a class are clustered.
Direct Text to Speech Translation System using Acoustic Units
This framework employs text in different source languages as input to generate speech in the target language without the need for text transcriptions in this language.
Improved Cross-Lingual Transfer Learning For Automatic Speech Translation
Having a single model that supports multiple translation tasks is desirable.
Deep Speech Enhancement for Reverberated and Noisy Signals using Wide Residual Networks
The DNN model, trained with artificial synthesized reverberation data, was able to deal with far-field reverberated speech from real scenarios.
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