Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
×
Jul 9, 2019 · We demonstrate that the multi-speaker ClariNet outperforms state-of-the-art systems in terms of naturalness, because the whole model is jointly ...
People also ask
Abstract: Recently, fully recurrent neural network (RNN) based end-to-end models have been proven to be effective for multi-speaker speech recognition in ...
Missing: Synthesis. | Show results with:Synthesis.
In this paper, we develop the first fully end-to-end, jointly trained deep learning system for separation and recognition of overlapping speech signals. The ...
Missing: Synthesis. | Show results with:Synthesis.
Jan 13, 2024 · In this paper, a multi-speaker text-to-speech synthesis using a generalized end-to-end loss function is developed, capable of generating speech in real-time.
Multi-speaker speech synthesis is a technique for modeling multiple speakers' voices with a single model. Although many.
Oct 19, 2024 · Abstract: Previous work on speaker adaptation for end-to-end speech synthesis still falls short in speaker similarity.
Apr 1, 2022 · We develop an end-to-end system for multi-channel, multi-speaker automatic speech recognition. We propose a frontend for joint source separation and ...
Missing: Synthesis. | Show results with:Synthesis.
In this paper, we propose a new sequence-to-sequence framework to directly decode multiple label sequences from a single speech sequence by unifying source ...
Missing: Synthesis. | Show results with:Synthesis.
Recent advances in end-to-end text-to-speech (TTS) synthesis enable the production of synthetic speech of high quality and good speaker similarity [1, 2, 3, 4].
Learning-based Text To Speech systems have the potential to generalize from one speaker to the next and thus require a relatively short sample of any new voice.