1 citations · 2 across the 8 of their papers we have counts for
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GANSpeech: Adversarial Training for High-Fidelity Multi-Speaker Speech Synthesis
Jinhyeok Yang, Jae-Sung Bae, Taejun Bak +2
Recent advances in neural multi-speaker text-to-speech (TTS) models have enabled the generation of reasonably good speech quality with a single model and made it possible to synthe…
Hierarchical Context-Aware Transformers for Non-Autoregressive Text to Speech
Jae-Sung Bae, Tae-Jun Bak, Young-Sun Joo +1
In this paper, we propose methods for improving the modeling performance of a Transformer-based non-autoregressive text-to-speech (TNA-TTS) model. Although the text encoder and aud…
FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis
Taejun Bak, Jae-Sung Bae, Hanbin Bae +2
Methods for modeling and controlling prosody with acoustic features have been proposed for neural text-to-speech (TTS) models. Prosodic speech can be generated by conditioning acou…
N-Singer: A Non-Autoregressive Korean Singing Voice Synthesis System for Pronunciation Enhancement
Gyeong-Hoon Lee, Tae-Woo Kim, Hanbin Bae +3
Recently, end-to-end Korean singing voice systems have been designed to generate realistic singing voices. However, these systems still suffer from a lack of robustness in terms of…
A Neural Text-to-Speech Model Utilizing Broadcast Data Mixed with Background Music
Hanbin Bae, Jae-Sung Bae, Young-Sun Joo +2
Recently, it has become easier to obtain speech data from various media such as the internet or YouTube, but directly utilizing them to train a neural text-to-speech (TTS) model is…