31 citations
- Institute of Cognitive and Brain SciencesUS2 papers
- The Ohio State UniversityUS2 papers
- Applications Research (United States)US1 paper
- Australian National UniversityAU1 paper
- Bellevue Hospital CenterUS1 paper
- Constructing ExcellenceGB1 paper
- Goldsmiths University of LondonGB1 paper
- Hefei UniversityCN1 paper
- MediaTek (China)CN1 paper
- Mitsubishi Electric Research Laboratories (United States)US1 paper
- Mitsubishi Electric (United States)US1 paper
- National Research University Higher School of EconomicsRU1 paper
Showing 2018Show all
3 papers · 1 filter
cs.SD2018★ 8 cited
Deep Learning Based Phase Reconstruction for Speaker Separation: A Trigonometric Perspective
Zhong-Qiu Wang, Ke Tan, DeLiang Wang
This study investigates phase reconstruction for deep learning based monaural talker-independent speaker separation in the short-time Fourier transform (STFT) domain. The key obser…
cs.IR2018
The DALPHI annotation framework & how its pre-annotations can improve annotator efficiency
Robert Greinacher, Franziska Horn
Producing the required amounts of training data for machine learning and NLP tasks often involves human annotators doing very repetitive and monotonous work. In this paper, we pres…
cs.SD2018★ 31 cited
End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction
Zhong-Qiu Wang, Jonathan Le Roux, DeLiang Wang +1
This paper proposes an end-to-end approach for single-channel speaker-independent multi-speaker speech separation, where time-frequency (T-F) masking, the short-time Fourier transf…