Adaptive blind moving source separation based on intensity vector statistics
- Submitting institution
-
Loughborough University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 2258
- Type
- D - Journal article
- DOI
-
10.1016/j.specom.2019.08.001
- Title of journal
- Speech Communication
- Article number
- -
- First page
- 1
- Volume
- 113
- Issue
- -
- ISSN
- 0167-6393
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work has been applied with a collaboration with HuSys Ltd. for a feasibility study of mission-critical situational awareness for the armed forces, and subsequently led to a joint bid with HuSys to the task of “Hearing Protection and Communication Issues” of DSTL’s Defence Human Capability Science & Technology Centre for further investigation and development (Managing Director, HuSys Ltd.,). The significance is further evidenced by consideration of this work by Samsung Electronics for its consumer product development (Digital Media R&D Center, Samsung Electronics Co. Ltd.,).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
