Research output per year
Research output per year
Personal profile
In Korean
이석진 교수(IT대학 전자공학부)
Education
o (2006) B.A., Seoul National University, Seoul, Republic of Korea
o (2008) M.A., Seoul National University, Seoul, Republic of Korea
o (2012) Ph.D., Seoul National University, Seoul, Republic of Korea
o (2008) M.A., Seoul National University, Seoul, Republic of Korea
o (2012) Ph.D., Seoul National University, Seoul, Republic of Korea
Professional Experience
o (2020~Present) Associate Professor, Kyungpook National University, Daegu, Republic of Korea
o (2018~2020) Assistant Professor, Kyungpook National University, Daegu, Republic of Korea
o (2014~2018) Assistant Professor, Kyonggi University, Gyeonggi-do, Republic of Korea
o (2012~2014) Senior Researcher, LG Electronics, Seoul, Republic of Korea
o (2018~2020) Assistant Professor, Kyungpook National University, Daegu, Republic of Korea
o (2014~2018) Assistant Professor, Kyonggi University, Gyeonggi-do, Republic of Korea
o (2012~2014) Senior Researcher, LG Electronics, Seoul, Republic of Korea
Research Interests
Acoustic Signal Processing, Adaptive Signal Processing, Array Signal Processing, Source Separation, Audio/Music Signal Processing, Signal processing for underwater acoustics, Deep Learning for acoustic signals, Music Information Retrieval
Major Research Achievements
o Development of acoustic signal processing and separation techniques based on nonnegative matrix factorization
o Development of feature extraction methods utilizing the signal characteristics for deep learning-based acoustic scene classifcation and sound event detection models
o Developing the deep learning-based compression methods for acoustic signals
o Research on the compressive sensing-based underwater acoustic signal processing techniques
o Reproduction of acoustic wavefield and binaural sound signals for immersive sound system
o Development of feature extraction methods utilizing the signal characteristics for deep learning-based acoustic scene classifcation and sound event detection models
o Developing the deep learning-based compression methods for acoustic signals
o Research on the compressive sensing-based underwater acoustic signal processing techniques
o Reproduction of acoustic wavefield and binaural sound signals for immersive sound system
url
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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벡터 양자화 변분 오토인코더 기반의 폴리 음향 생성 모델을 위한 잔여 벡터 양자화 적용 연구
Translated title of the contribution :A study on the application of residual vector quantization for vector quantized-variational autoencoder-based foley sound generation model Research output: Contribution to journal › Article › peer-review
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음고 개수 정보 활용을 통한 기계학습 기반 자동악보전사 모델의 성능 개선 연구
Translated title of the contribution :A study on improving the performance of the machine-learning based automatic music transcription model by utilizing pitch number information Research output: Contribution to journal › Article › peer-review
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Experimental performance analysis on the non-negative matrix factorization-based continuous wave reverberation suppression according to hyperparameters
Lee, S., 2023, In: Journal of the Acoustical Society of Korea. 42, p. 32Research output: Contribution to journal › Article › peer-review
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비음수행렬분해 기반 연속파 잔향 제거 기법의 초매개변숫값에 따른 실험적 성능 분석
Translated title of the contribution :Experimental performance analysis on the non-negative matrix factorization-based continuous wave reverberation suppression according to hyperparameters Research output: Contribution to journal › Article › peer-review
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Data Augmentation using Checked Pattern Mask for Acoustic Scene Classification
Baek, S. & Lee, S., 2022, In: Proceedings of the International Congress on Acoustics.Research output: Contribution to journal › Conference article › peer-review