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Found 4 papers, 0 papers with code
Transduce and Speak: Neural Transducer for Text-to-Speech with Semantic Token Prediction
We introduce a text-to-speech(TTS) framework based on a neural transducer.
Fully Unsupervised Training of Few-shot Keyword Spotting
For training a few-shot keyword spotting (FS-KWS) model, a large labeled dataset containing massive target keywords has known to be essential to generalize to arbitrary target keywords with only a few enrollment samples.
Disentangled Speaker Representation Learning via Mutual Information Minimization
The experimental results show that fine-tuning with a disentanglement framework on a existing pre-trained model is valid and can further improve performance.
Bootstrap Equilibrium and Probabilistic Speaker Representation Learning for Self-supervised Speaker Verification
In this paper, we propose self-supervised speaker representation learning strategies, which comprise of a bootstrap equilibrium speaker representation learning in the front-end and an uncertainty-aware probabilistic speaker embedding training in the back-end.
