Factors Affecting the Overall Voice Quality in .NET

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11.4.5 Factors Affecting the Overall Voice Quality
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The network delay, packet losses, packet jitters, and echoes are the major contributors to the perceived quality of VoIP. The ITU G.114 standard states that the end-to-end one-way delay should not exceed 150 ms. The overall voice packet delay can be improved with prioritizing the voice in the network packet. The speech-coding algorithms can also compensate these factors. Furthermore, ef cient packet-loss concealment algorithms make the lost or discarded packet effects less noticeable. The delay can also be shortened by choosing low-delay speech CODECs which use small buffer size for block processing. A good jitter buffer algorithm can effectively compensate the jitter with the minimum buffer size to make the overall delay minimized. Network echoes can be effectively canceled or suppressed using adaptive echo cancelation algorithms introduced in 10.
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11.5 Experiments and Program Examples
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In this section, we will calculate the LPC coef cients using MATLAB, C, and C55x programs.
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11.5.1 Calculating LPC Coef cients Using Floating-Point C
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In this experiment, we implement the Levinson Durbin algorithm using oating-point C to calculate the LPC coef cients. The main C program to access these functions is listed in Table 11.12, where three functions calc_autoc( ), calc_lpc( ), and hmwindowing( ) are used to calculate the LPC
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Statistic of RTP data. It shows there are 336 RTP packets without packet loss and sequence errors
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Table 11.12 Main program lpc_mainTest.c for computing LPC coef cients
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while (fread(input,sizeof(short),N,fpin)==N) { // Apply the Hamming window hmwindowing(N,input,ws); // Autocorrelation calc_autoc(ws, p_order, N,R); // Levension_Durbin calc_lpc( R, lpc, p_order); }
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coef cients. Function calc_lpc( ) is listed in Table 11.13. The les used for this experiment are listed in Table 11.14. Procedures of the experiment are listed as follows: 1. Start CCS, open the project, build, and load the program. 2. Edit the experiment parameter le param.txt located in the data directory, include input speech le, output coef cients le, LPC order, and frame size if necessary. The default setting uses the speech le voice4.pcm, 10th-order LPC, and frame size 180. 3. Modify the experiment test program such that the envelope of LPC coef cients will be plotted by CCS and displayed. The envelope will look similar to Figure 11.2. 4. Repeat the experiment with different speech les, such as male and female speakers, voiced and unvoiced segments.
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11.5.2 Calculating LPC Coef cients Using C55x Intrinsics
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A special library such as the ETSI (Europe Telecommunication Standard Institute) library can be used to represent the xed-point operations for the CODECs including the G.723.1, G.729, and AMR. By using the basic operators de ned in the ETSI library, the oating-point C code can be converted to xed-point C code. The oating-point C code must be modi ed for implementation on the xed-point C55x. The input signal is normalized to maximally use the limited dynamic range and to avoid over ow. A vector normalization example is shown in Table 11.15. In the code, functions round, norm_l, L_add, L_sub, L_shl, and L_shr are used to simulate the processor operations of rounding, 16-bit normalization, 32-bit addition, subtraction, and 32-bit left and right shifts. After normalization, the Levinson algorithm is used to compute LPC coef cients. An example of calculating analysis lter coef cients is shown in Table 11.15. The xed-point C libraries do not have the ef ciency that a DSP processor requires for real-time processing. Using the C55x intrinsics to replace functions in the xed-point C libraries, we can achieve much better run-time ef ciency. The results from xed-point C implementation and intrinsics implementation are bit exact. This ensures the CODEC implementations in both xed-point C and C55 intrinsics to have the same performance. In Table 11.15, the operator round(x) converts a 32-bit data to 16 bits with rounding of the higher 16-bit word. Operator norm_l(x) calculates the leading sign bit. Using the same approach, the Levinson Durbin algorithm can be converted as listed in Table 11.16. In the program, the LPC coef cients a[ ] and the re ection coef cients K[ ] are represented in Q.13 format to work with the LPC coef cients between 4 (0x8000/0x2000) and +3 8191 (0x7fff/0x2000). The prediction error E[ ] and correlation 8192 R[ ] are in Q.14 format to avoid over ow. The les used for this experiment are listed in Table 11.17.
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