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Found 6 papers, 0 papers with code
Preference-based training framework for automatic speech quality assessment using deep neural network
We propose a training framework of SQA models that can be trained with only preference scores derived from pairs of MOS to improve ranking prediction.
NASTAR: Noise Adaptive Speech Enhancement with Target-Conditional Resampling
NASTAR uses a feedback mechanism to simulate adaptive training data via a noise extractor and a retrieval model.
SVSNet: An End-to-end Speaker Voice Similarity Assessment Model
Neural evaluation metrics derived for numerous speech generation tasks have recently attracted great attention.
Relational Data Selection for Data Augmentation of Speaker-dependent Multi-band MelGAN Vocoder
Nowadays, neural vocoders can generate very high-fidelity speech when a bunch of training data is available.
The AS-NU System for the M2VoC Challenge
The first track focuses on using a small number of 100 target utterances for voice cloning, while the second track focuses on using only 5 target utterances for voice cloning.
The Academia Sinica Systems of Voice Conversion for VCC2020
This paper describes the Academia Sinica systems for the two tasks of Voice Conversion Challenge 2020, namely voice conversion within the same language (Task 1) and cross-lingual voice conversion (Task 2).
