Hybrid multimode/multirate CS-ACELP speech coding for adaptive voice over IP
Speech Communication
Intrastandard Hybrid Speech Coding for Adaptive IP Telephony
QoS-IP '01 Proceedings of the International Workshop on Quality of Service in Multiservice IP Networks
Verifier-tuple for audio-forensic to determine speaker environment
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Presence: Teleoperators and Virtual Environments
Toward a sound analysis system for telemedicine
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Environmental sounds classification based on visual features
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Environment dependent noise tracking for speech enhancement
International Journal of Speech Technology
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Background environmental noises degrade the performance of speech-processing systems (e.g. speech coding, speech recognition). By modifying the processing according to the type of background noise, the performance can be enhanced. This requires noise classification. In this paper, four pattern-recognition frameworks have been used to design noise classification algorithms. Classification is done on a frame-by-frame basis (e.g. once every 20 ms). Five commonly encountered noises in mobile telephony (i.e. car, street, babble, factory, and bus) have been considered in our study. Our experimental results show that the line spectral frequencies (LSFs) are robust features in distinguishing the different classes of noises.