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2016 ICME:Phonetic posteriorgrams for many-to-one voice conversion without parallel data training
時間 2021-01-11
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作者: Helen Meng 單位:港中文 abstract 非平行訓練數據進行voice conversion 首先用一個SI-ASR(speaker-independent 語音識別系統)提取PPGs(Phonetic PosteriorGrams),這個PPGs可以對應於說話者的發音,並且對應於獨立說話者的 說話內容。 然後用DBLSTM(deep bi-LSTM)建模PPGs和target
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相關文章
1.
SINGING VOICE CONVERSION WITH NON-PARALLEL DATA
2.
Odessey2018:Average Modeling Approach to Voice Conversion with Non-Parallel Data
3.
2019trans--Sequence-to-Sequence Acoustic Modeling for Voice Conversion
4.
StarGAN-VC: non-parallel many-to-many voice conversion with StaGAN
5.
AdaGAN:adaptive GAN for many-to-many non-parallel voice converison
6.
StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
7.
ONE-SHOT VOICE CONVERSION USING STAR-GAN
8.
Whether To Pretrain DNN or Not?: An Empirical Analysis for Voice Conversion
9.
Parallel-data-free voice conver- sion using cycle-consistent adversarial networks
10.
【每週論文】Graphene: Packing and Dependency-aware Scheduling for Data-Parallel Clusters(OSDI 2016)
>>更多相關文章<<