Any-to-many voice conversion with location-relative sequence-to-sequence modeling
This paper proposes an any-to-many location-relative, sequence-to-sequence (seq2seq),
non-parallel voice conversion approach, which utilizes text supervision during training. In …
non-parallel voice conversion approach, which utilizes text supervision during training. In …
Non-parallel sequence-to-sequence voice conversion with disentangled linguistic and speaker representations
This article presents a method of sequence-to-sequence (seq2seq) voice conversion using
non-parallel training data. In this method, disentangled linguistic and speaker …
non-parallel training data. In this method, disentangled linguistic and speaker …
ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion
This article proposes a voice conversion (VC) method using sequence-to-sequence
(seq2seq or S2S) learning, which flexibly converts not only the voice characteristics but also …
(seq2seq or S2S) learning, which flexibly converts not only the voice characteristics but also …
Duration controllable voice conversion via phoneme-based information bottleneck
Several voice conversion (VC) methods using a simple autoencoder with a carefully
designed information bottleneck have recently been studied. In general, they extract content …
designed information bottleneck have recently been studied. In general, they extract content …
Any-to-one sequence-to-sequence voice conversion using self-supervised discrete speech representations
We present a novel approach to any-to-one (A2O) voice conversion (VC) in a sequence-to-
sequence (seq2seq) framework. A2O VC aims to convert any speaker, including those …
sequence (seq2seq) framework. A2O VC aims to convert any speaker, including those …
Pretraining techniques for sequence-to-sequence voice conversion
Sequence-to-sequence (seq2seq) voice conversion (VC) models are attractive owing to
their ability to convert prosody. Nonetheless, without sufficient data, seq2seq VC models can …
their ability to convert prosody. Nonetheless, without sufficient data, seq2seq VC models can …
The sequence-to-sequence baseline for the voice conversion challenge 2020: Cascading asr and tts
This paper presents the sequence-to-sequence (seq2seq) baseline system for the voice
conversion challenge (VCC) 2020. We consider a naive approach for voice conversion (VC) …
conversion challenge (VCC) 2020. We consider a naive approach for voice conversion (VC) …
Voice transformer network: Sequence-to-sequence voice conversion using transformer with text-to-speech pretraining
We introduce a novel sequence-to-sequence (seq2seq) voice conversion (VC) model based
on the Transformer architecture with text-to-speech (TTS) pretraining. Seq2seq VC models …
on the Transformer architecture with text-to-speech (TTS) pretraining. Seq2seq VC models …
S2VC: A framework for any-to-any voice conversion with self-supervised pretrained representations
Any-to-any voice conversion (VC) aims to convert the timbre of utterances from and to any
speakers seen or unseen during training. Various any-to-any VC approaches have been …
speakers seen or unseen during training. Various any-to-any VC approaches have been …
AttS2S-VC: Sequence-to-sequence voice conversion with attention and context preservation mechanisms
This paper describes a method based on a sequence-to-sequence learning (Seq2Seq) with
attention and context preservation mechanism for voice conversion (VC) tasks. Seq2Seq …
attention and context preservation mechanism for voice conversion (VC) tasks. Seq2Seq …