Search Results for author: Minchan Kim

Found 5 papers, 0 papers with code

Adversarial Speaker-Consistency Learning Using Untranscribed Speech Data for Zero-Shot Multi-Speaker Text-to-Speech

no code implementations12 Oct 2022 Byoung Jin Choi, Myeonghun Jeong, Minchan Kim, Sung Hwan Mun, Nam Soo Kim

Several recently proposed text-to-speech (TTS) models achieved to generate the speech samples with the human-level quality in the single-speaker and multi-speaker TTS scenarios with a set of pre-defined speakers.

Fully Unsupervised Training of Few-shot Keyword Spotting

no code implementations6 Oct 2022 Dongjune Lee, Minchan Kim, Sung Hwan Mun, Min Hyun Han, Nam Soo Kim

For training a few-shot keyword spotting (FS-KWS) model, a large labeled dataset containing massive target keywords has known to be essential to generalize to arbitrary target keywords with only a few enrollment samples.

Keyword Spotting Metric Learning +1

Disentangled Speaker Representation Learning via Mutual Information Minimization

no code implementations17 Aug 2022 Sung Hwan Mun, Min Hyun Han, Minchan Kim, Dongjune Lee, Nam Soo Kim

The experimental results show that fine-tuning with a disentanglement framework on a existing pre-trained model is valid and can further improve performance.

Disentanglement Speaker Recognition +1

Expressive Text-to-Speech using Style Tag

no code implementations1 Apr 2021 Minchan Kim, Sung Jun Cheon, Byoung Jin Choi, Jong Jin Kim, Nam Soo Kim

In this work, we propose StyleTagging-TTS (ST-TTS), a novel expressive TTS model that utilizes a style tag written in natural language.

Language Modelling TAG

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