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Microphone wind noise reduction using singular spectrum analysis techniques (2017)
Presentation / Conference
Eldwaik, O., & Li, F. (2017, November). Microphone wind noise reduction using singular spectrum analysis techniques. Presented at 33nd Annual Conference And Exhibition. Reproduced Sound 2017 : Sound Quality By Design, Nottingham, UK

Wind noise is a known problem that contaminates microphone signals in many field measurement and audio recording scenarios. A recently completed EPSRC project has led to the development of a tool to detect such noise; this paper takes a step further... Read More about Microphone wind noise reduction using singular spectrum analysis techniques.

Robust speaker verification in reverberant conditions using estimated acoustic parameters : a maximum likelihood estimation and training on the fly approach (2017)
Presentation / Conference
Yousif, K., & Li, F. (2017, August). Robust speaker verification in reverberant conditions using estimated acoustic parameters : a maximum likelihood estimation and training on the fly approach. Presented at 7th International Conference on Innovative Computing Technology (INTECH 2017), Luton, UK

Speaker recognition has been developed into a relatively mature state over the past few decades through continuous research and development work. Existing methods typically use the robust features extracted from noise and reverberation free speech si... Read More about Robust speaker verification in reverberant conditions using estimated acoustic parameters : a maximum likelihood estimation and training on the fly approach.

Mitigating wind noise in outdoor microphone signals using a singular spectral subspace method (2017)
Presentation / Conference
Eldwaik, O., & Li, F. (2017, August). Mitigating wind noise in outdoor microphone signals using a singular spectral subspace method. Presented at IEEE, Seventh International Conference on Innovative Computing Technology (INTECH 2107), Luton, UK

Wind noise is one of the major concerns of outdoor microphone signal acquisition. Filtering and removal of wind noise are known to be difficult due to its broadband and time varying nature. This paper proposes the use of singular spectrum analysis to... Read More about Mitigating wind noise in outdoor microphone signals using a singular spectral subspace method.

Training "on the fly" to improve the performance of speaker recognition in noisy environments (2017)
Book Chapter
Al-Noori, A., Duncan, P., & Li, F. (2017). Training "on the fly" to improve the performance of speaker recognition in noisy environments. In Proceedings: 2017 AES International Conference on Audio Forensics. Audio Engineering Society

Reliability of Speaker Recognition (SR) is crucial for critical applications, especially in adverse acoustic conditions. Ambient noises and their variations represent a significant challenge for such applications. In this paper, a new technique is... Read More about Training "on the fly" to improve the performance of speaker recognition in noisy environments.