Search Results for author: Ohsung Kwon

Found 3 papers, 1 papers with code

Effective parameter estimation methods for an ExcitNet model in generative text-to-speech systems

1 code implementation21 May 2019 Ohsung Kwon, Eunwoo Song, Jae-Min Kim, Hong-Goo Kang

In this paper, we propose a high-quality generative text-to-speech (TTS) system using an effective spectrum and excitation estimation method.

Speech Synthesis Text-To-Speech Synthesis

TTS-by-TTS 2: Data-selective augmentation for neural speech synthesis using ranking support vector machine with variational autoencoder

no code implementations30 Jun 2022 Eunwoo Song, Ryuichi Yamamoto, Ohsung Kwon, Chan-Ho Song, Min-Jae Hwang, Suhyeon Oh, Hyun-Wook Yoon, Jin-Seob Kim, Jae-Min Kim

In the proposed method, we first adopt a variational autoencoder whose posterior distribution is utilized to extract latent features representing acoustic similarity between the recorded and synthetic corpora.

Speech Synthesis

Unified Speech-Text Pretraining for Spoken Dialog Modeling

no code implementations8 Feb 2024 Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, Ohsung Kwon, Jungwhan Kim, Jaehong Lee, Eunwoo Song, Myungwoo Oh, Sungroh Yoon, Kang Min Yoo

While recent work shows promising results in expanding the capabilities of large language models (LLM) to directly understand and synthesize speech, an LLM-based strategy for modeling spoken dialogs remains elusive and calls for further investigation.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

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