3 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
The NPU-MSXF Speech-to-Speech Translation System for IWSLT 2023 Speech-to-Speech Translation Task
Kun Song, Yi lei, Peikun Chen +6
This paper describes the NPU-MSXF system for the IWSLT 2023 speech-to-speech translation (S2ST) task which aims to translate from English speech of multi-source to Chinese speech.…
StyleS2ST: Zero-shot Style Transfer for Direct Speech-to-speech Translation
Kun Song, Yi Ren, Yi Lei +5
Direct speech-to-speech translation (S2ST) has gradually become popular as it has many advantages compared with cascade S2ST. However, current research mainly focuses on the accura…
Robust MelGAN: A robust universal neural vocoder for high-fidelity TTS
Kun Song, Jian Cong, Xinsheng Wang +4
In current two-stage neural text-to-speech (TTS) paradigm, it is ideal to have a universal neural vocoder, once trained, which is robust to imperfect mel-spectrogram predicted from…
DSPGAN: a GAN-based universal vocoder for high-fidelity TTS by time-frequency domain supervision from DSP
Kun Song, Yongmao Zhang, Yi Lei +5
Recent development of neural vocoders based on the generative adversarial neural network (GAN) has shown obvious advantages of generating raw waveform conditioned on mel-spectrogra…
AdaVITS: Tiny VITS for Low Computing Resource Speaker Adaptation
Kun Song, Heyang Xue, Xinsheng Wang +6
Speaker adaptation in text-to-speech synthesis (TTS) is to finetune a pre-trained TTS model to adapt to new target speakers with limited data. While much effort has been conducted…