• Title/Summary/Keyword: 패킷 손실 은닉

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Performance Improvement of Packet Loss Concealment Algorithm in G.711 Using Speech Characteristics (음성 특성을 이용한 G.711 패킷 손실 은닉 알고리즘의 성능개선)

  • Han Seung-Ho;Kim Jin-Sul;Lee Hyun-Woo;Ryu Won;Hahn Min-Soo
    • MALSORI
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    • no.57
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    • pp.175-189
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    • 2006
  • Because a packet loss brings about degradation of speech quality, VoIP speech coders have PLC (Packet Loss Concealment) mechanism. G.711, which is a mandatory VoIP speech coder, also has the PLC algorithm based on pitch period replication. However, it is not robust to burst losses. Thus, we propose two methods to improve the performance of the original PLC algorithm in G.711. One adaptively utilizes voiced/unvoiced information of adjacent good frames regarding to the current lost frame. The other is based on adaptive gain control according to energy variation across the frames. We evaluate the performance of the proposed PLC algorithm by measuring a PESQ value under different random and burst packet loss simulating conditions. It is shown from the experiments that the performance of the proposed PLC algorithm outperforms that of PLC employed in ITU-T Recommendation G.711.

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Home monitoring system based on sound event detection for the hard-of-hearing (청각장애인을 위한 사운드 이벤트 검출 기반 홈 모니터링 시스템)

  • Kim, Gee Yeun;Shin, Seung-Su;Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.4
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    • pp.427-432
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    • 2019
  • In this paper, we propose a home monitoring system using sound event detection based on a bidirectional gated recurrent neural network for the hard-of-hearing. First, in the proposed system, packet loss concealment is used to recover a lost signal captured through wireless sensor networks, and reliable channels are selected using multi-channel cross correlation coefficient for effective sound event detection. The detected sound event is converted into the text and haptic signal through a harmonic/percussive sound source separation method to be provided to hearing impaired people. Experimental results show that the performance of the proposed sound event detection method is superior to the conventional methods and the sound can be expressed into detailed haptic signal using the source separation.