Search Results
Generalized End-to-End Loss for Speaker Verification
CorentinJ/Real-Time-Voice-Cloning
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In this paper, we propose a new loss function called generalized end-to-end (GE2E) loss, which makes the training of speaker verification models more efficient than our previous tuple-based end-to-end (TE2E) loss function.
Ranked #1 on
Speaker Verification
on CALLHOME
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
CorentinJ/Real-Time-Voice-Cloning
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NeurIPS 2018
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Tacotron: Towards End-to-End Speech Synthesis
CorentinJ/Real-Time-Voice-Cloning
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A text-to-speech synthesis system typically consists of multiple stages, such as a text analysis frontend, an acoustic model and an audio synthesis module.
Ranked #5 on
Speech Synthesis
on North American English
Efficient Neural Audio Synthesis
CorentinJ/Real-Time-Voice-Cloning
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ICML 2018
The small number of weights in a Sparse WaveRNN makes it possible to sample high-fidelity audio on a mobile CPU in real time.
