no code implementations • 23 May 2024 • Suyoung Kim, Jiyeon Hwang, Ho-Young Jung
Recently, deep end-to-end learning has been studied for intent classification in Spoken Language Understanding (SLU).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +6
no code implementations • 5 May 2024 • June-Woo Kim, Miika Toikkanen, Sangmin Bae, Minseok Kim, Ho-Young Jung
To address this, we propose RepAugment, an input-agnostic representation-level augmentation technique that outperforms SpecAugment, but is also suitable for respiratory sound classification with waveform pretrained models.
1 code implementation • 15 Dec 2023 • June-Woo Kim, Sangmin Bae, Won-Yang Cho, Byungjo Lee, Ho-Young Jung
Despite the remarkable advances in deep learning technology, achieving satisfactory performance in lung sound classification remains a challenge due to the scarcity of available data.
Ranked #3 on Audio Classification on ICBHI Respiratory Sound Database (using extra training data)
1 code implementation • 11 Nov 2023 • June-Woo Kim, Chihyeon Yoon, Miika Toikkanen, Sangmin Bae, Ho-Young Jung
In this work, we propose a straightforward approach to augment imbalanced respiratory sound data using an audio diffusion model as a conditional neural vocoder.
Ranked #2 on Audio Classification on ICBHI Respiratory Sound Database (using extra training data)
1 code implementation • 5 Feb 2020 • June-Woo Kim, Ho-Young Jung, Minho Lee
The additional pre/post processing such as MFB and vocoder is not essential to convert real human speech to others.