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Jae-Mo Yang
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2020 – today
- 2022
- [j4]Joo-Hyun Lee, Joon-Hyuk Chang, Jae-Mo Yang, Han-Gil Moon:
NAS-TasNet: Neural Architecture Search for Time-Domain Speech Separation. IEEE Access 10: 56031-56043 (2022) - [c3]Jae-Mo Yang, G. W. Lee, Sangeun Kim, Han-Gil Moon:
MULTI-SENSOR SPEECH ENHANCEMENT USING IN-EAR AND BEAMFORMING SIGNAL SYNTHESIS IN TWS VOICE COMMUNICATION. ICCE 2022: 1-6 - [i1]Won-Gook Choi, Joon-Hyuk Chang, Jae-Mo Yang, Han-Gil Moon:
Instance-level loss based multiple-instance learning for acoustic scene classification. CoRR abs/2203.08439 (2022)
2010 – 2019
- 2014
- [j3]Jae-Mo Yang, Hong-Goo Kang:
An Efficient Multichannel Linear Prediction-Based Blind Equalization Algorithm in Near Common Zeros Condition. IEEE Signal Process. Lett. 21(3): 306-310 (2014) - [j2]Jae-Mo Yang, Hong-Goo Kang:
Online Speech Dereverberation Algorithm Based on Adaptive Multichannel Linear Prediction. IEEE ACM Trans. Audio Speech Lang. Process. 22(3): 608-619 (2014) - 2013
- [c2]Jae-Mo Yang, Hong-Goo Kang:
Adaptive multichannel linear prediction based dereverberation in time-varying room environments. EUSIPCO 2013: 1-5 - 2012
- [j1]Jae-Mo Yang, Hong-Goo Kang:
Two-stage source tracking method using a multiple linear regression model in the expanded phase domain. EURASIP J. Adv. Signal Process. 2012: 5 (2012)
2000 – 2009
- 2009
- [c1]Jae-Mo Yang, Chang-Heon Lee, Seungil Kim, Hong-Goo Kang:
A robust time difference of arrival estimator in reverberant environments. EUSIPCO 2009: 864-868
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