Adaptive Speech Streaming Based on Speech Quality Estimation and Artificial Bandwidth Extension for Voice over Wireless Multimedia Sensor Networks

Abstract

In this paper, an adaptive speech streaming method is proposed to improve the perceived speech quality (PSQ) of voice over wireless multimedia sensor network (WMSNs). First of all, the proposed method estimates the PSQ of the received speech data under different network conditions that are represented by the packet loss rates (PLRs). Simultaneously, the proposed method classifies the speech signal as either an onset or a nononset frame. Based on the estimated PSQ and the speech class, it determines an appropriate bit rate for the redundant speech data (RSD) that are transmitted with the primary speech data (PSD) to help reconstruct the speech signals of any lost frames. In particular, when the estimated PLR is high, the bit rate of the RSD should be increased by decreasing that of the PSD. Thus, the bandwidth of the PSD is changed from wideband to narrowband, and an artificial bandwidth extension technique is applied to the decoded narrowband speech. It is shown from the simulation that the proposed method significantly improves the decoded speech quality under packet loss conditions in a WMSN, compared to a decoder-based packet loss concealment method and a conventional redundant speech transmission method.

Adaptive Speech Streaming Based on Packet Loss Prediction Using Support Vector Machine for Software-Based Multipoint Control Unit over IP Networks

“…The PSQE-based ASSM begins by estimating the PSQ, which is a good indicator of the current PLR. Therefore, a lowdelayed version of the nonintrusive PSQ assessment method defined in ITU-T Recommendation P.563 is used to estimate the PSQ as a mean opinion score (MOS) without using a reference speech signal [13].…”

“…The performance of the proposed PLP-based ASSM within the equivalent transmission bandwidth was compared with those of two conventional speech streaming methods: a decoder-based PLC method [10] and a sender-based RST method [6], and the PSQE-based ASSM [13]. The decoderbased PLC method encoded speech signals using the AMR-NB encoder at 10.2 kb/s with no RSD bitstream.…”

“…To utilize the advantages of both schemes, an adaptive speech streaming method (PSQE-based ASSM) was proposed to adaptively transmit redundant speech data (RSD) based on a real-time PSQ estimation under current network conditions [13]. The PSQE-based ASSM determines a suitable RST mode based on the PSQ estimation for the current PLR, and then generates the bitstreams of primary speech data (PSD) and RSD using a multirate speech coder to maintain the equivalent transmission bitrate.…”

“…Finally, Section V provides some concluding remarks regarding this research. Figure 1 shows a block diagram and the packet flow of a speech streaming system employing PSQE-based ASSM [13]. As the speech signal PSD(n) comes into an input device at the sender side of a speech streaming system, it is classified as either an onset frame or a non-onset frame.…”

Reliability evaluation of wireless multimedia sensor networks based on instantaneous availability

“…In the past few decades, the Internet of things (IoT) plays an increasingly important role in changing peoples’ lifestyles and promoting the development of information technology. 1,2 Compared with the traditional wireless sensor networks (WSNs), wireless multimedia sensor networks (WMSNs) have stronger capability of picking up information in IoT with the characteristics of rich sources of information, 3 flexible network structure, 4 and fusion of heterogeneous data, 5,6 which has been widely applied in key infrastructure areas such as intelligent transportation, 7 smart grid, 8 telehealth, 9 and automated factory. 10 WMSN is a typically distributed complex network system containing multimedia sensor nodes and control center which can be abstracted into a network graph composed of nodes and edges.…”