Wen-Chin Huang,Tomoki Hayashi,Yi-Chiao Wu,Hirokazu Kameoka,Tomoki Toda, Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining, arXiv, 2019 Synthesized data! 比如批量的将收集到的很多人说话的语句都用谷歌小姐说一遍,然后训练一个模型可以把所有...
《Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining》W Huang, T Hayashi, Y Wu, H Kameoka, T Toda [Nagoya University & NTT Communicat...
Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretrainingdoi:10.21437/INTERSPEECH.2020-1066Wen-Chin HuangTomoki HayashiYi-Chiao WuHirokazu KameokaTomoki TodaISCAConference of the International Speech Communication Association...
Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining Sequence-to-sequence (seq2seq) voice conversion (VC) models have great potential for electrolaryngeal (EL) speech to normal speech converison (EL2SP). Howe... WC Huang,T Hayashi,YC...
Support to more than 40 AI voices for text-to-audio conversion. Steps to Use Wondershare DemoCreator's AI Voice Changer Download and open Wondershare DemoCreator. Click theVideo Editor>My Librarytab on the menu bar, and click the "+" button to upload your audio or video files. ...
In this work, we propose a variant of STARGAN for many-to-many voice conversion (VC) conditioned on the d-vectors for short-duration (2-15 seconds) speech. We make several modifications to the STARGAN training and employ new network architectures. We employ a transformer encoder in the ...
Conversion-WebUI-main/logs/vaclavknop_hisvoice', 'False', '3.0'] ['D:\\Oculus\\Retrieval-based-Voice-Conversion-WebUI-main\\infer\\modules\\train\\preprocess.py', 'C:\\Users\\user\\Documents\\HisVOICE\\in', '40000', '10', 'D:\\Oculus\\Retrieval-based-Voice-Conversion-WebUI-main...
The longer the past voice is, the better the accuracy of the conversion, but the longer the res is, the longer the calculation takes. (Probably because Transformer is a bottleneck, the calculation time will increase by the square of this length) Detail is [here](https://github.com/w-...
Adversarial Speaker Disentanglement Using Unannotated External Data for Self-supervised Representation Based Voice Conversion Multilingual Speech Synthesis and Cross-Language Voice Cloning: GRL RoFormer: Enhanced Transformer with rotary position embedding Method of Preventing Timbre Leakage Based on Data Perturbatio...
Many-to-many Cross-lingual Voice Conversion with a Jointly Trained Speaker Embedding Network 三种经典方法: (1)average model用新的说话人的句子进行自适应,但是由于两种语言之间的gap,会有较大的失真。 (2)用i-vector拼接在输入特征上,网络学习说话人独立的特征映射。但是i-vector提取的模型是单独的sv loss...