In this paper, we introduce hidden Markov model (HMM) based packet loss concealment (PLC) methods and discuss the impact of Markovian assumptions on the performance of these models. We also present a new PLC method, implemented on the G.722.2 codec, which relies on the HMM and Decision Tree (DT), namely HMDT architecture, to enhance the perceptual quality of Voice over Internet Protocol (VoIP) communications under severe packet loss conditions. The proposed method is a receiver-based model that tracks the statistical evolution of speech signals through HMM and uses the DT architecture to predict/estimate accurately the lost speech packets by exploiting the surrounding received speech packets. Objective and subjective metrics are used to evaluate the performance of the proposed method. Test results show that our proposed method enhances considerably the speech quality of the reconstructed speech signal and produces a more natural speech variation compared to conventional PLC methods.
Forward Error Correction (FEC) is a packet loss concealment (PLC) mechanism used to recover lost packets via the transmission of a set of redundant packets along with the original ones. Given its performance in improving the end-to-end error recovery capability of lossy networks as well as maximizing the end-to-end quality of service (QoS), FEC is usually considered to be an interesting choice for real-time applications like voice over Internet protocol (VoIP). Note that this mechanism has a low efficiency against consecutive packet losses, which heavily affects the perceptual speech quality in a VoIP environment and could even produce a total desynchronization between the coder and the decoder. The objective of this paper is to introduce a new FEC scheme that can address the aforementioned issue. We use also a Time Scale Modification (TSM) procedure that enhance the performance of our proposed FEC scheme in order to further improve the performance of our scheme under severe network conditions. Subjective and objective evaluation metrics are used to evaluate the efficiency of the proposed method. Results show that the new FEC method achieves a Perceptual evaluation of speech quality (PESQ) value exceeding 3.5 at a 10% frame erasure rate with a noticeable enhancement in voice perception.
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