多媒體網路與系統實驗室

Inferring Speech Activities from Encrypted Skype Traffic

(NOTE: Sheng-Wei Chen is also known as Kuan-Ta Chen.)

Abstract

Normally, voice activity detection (VAD) refers to speech processing algorithms for detecting the presence or absence of human speech in segments of audio signals. In this paper, however, we focus on speech detection algorithms that take VoIP traffic instead of audio signals as input. We call this category of algorithms network-level VAD.

Traditional VAD usually plays a fundamental role in speech processing systems because of its ability to delimit speech segments. Network-level VAD, on the other hand, can be quite helpful in network management, which is the motivation for our study. We propose the first real-time network-level VAD algorithm that can extract voice activity from encrypted and non-silence-suppressed Skype traffic. We evaluate the speech detection accuracy of the proposed algorithm with extensive reallife traces. The results show that our scheme achieve reasonably good performance even high degree of randomness has been injected into the network traffic.

Yu-Chun Chang, Kuan-Ta Chen, Chen-Chi Wu, and Chin-Laung Lei, "Inferring Speech Activities from Encrypted Skype Traffic," In Proceedings of IEEE Globecom 2008, 2008.

@INPROCEEDINGS{chang08:speech,
  AUTHOR     = {Yu-Chun Chang and Kuan-Ta Chen and Chen-Chi Wu and Chin-Laung Lei},
  TITLE      = {Inferring Speech Activities from Encrypted Skype Traffic},
  BOOKTITLE = {Proceedings of IEEE Globecom 2008},
  YEAR       = {2008}
}

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