An intelligent system for spoken term detection that uses belief combination
- Submitting institution
-
University of Central Lancashire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 16499
- Type
- D - Journal article
- DOI
-
10.1109/MIS.2017.13
- Title of journal
- IEEE Intelligent Systems
- Article number
- -
- First page
- 70
- Volume
- 32
- Issue
- 1
- ISSN
- 1541-1672
- Open access status
- Technical exception
- Month of publication
- February
- Year of publication
- 2017
- 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
-
1
- Research group(s)
-
A - Aerospace and Sensing Group
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents various novel techniques for continuous speech recognition and mitigates the shortcomings of existing spoken term detection methods. It has driven a new area of interest in this subject where particular spoken terms (e.g. related to terrorism) can be distinguished from speech with high accuracy rates to help trigger appropriate actions. This has prompted the development of similar techniques and several patent applications (Patent Numbers. EP3570536, EP3570537) within industry.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
