Abstract
In this paper, we propose a novel double-talk detection (DTD) technique based on a soft decision in the frequency domain. The proposed method provides an efficient procedure to detect the double-talk situation by the use of the global near-end speech presence probability (GNSPP) and voice activity detection (VAD) of the near-end and far-end signal. Specifically, the GNSPP is derived based on a statistical method of speech and is employed to determine the double-talk presence in a given frame. The performance of our approach is evaluated by objective tests under different environments, and it is found that the suggested method yields better results compared with the conventional scheme.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
