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Figure 3-6 A quantization error
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than to 50 and we could send the bit representation for 55 This method can easily approach the stage of diminishing returns The more accurate we want the samples to be, the more bits we need to represent each sample and the more bandwidth we need Alternatively, we can use relatively few bits, but we can use them in a more sophisticated manner If we look at the possible range of signal levels in speech and if we want to apply uniform quantization levels, then we have two effects First, we would need many bits to represent each sample, and second, loud talkers would sound better than quiet talkers The latter is because the effect of quantization noise is less at higher levels than at lower levels For example, the detrimental effect of digitizing a sample of 112 as the value 11 (about 18 percent too low) is a lot less than the effect of digitizing a sample of 22 as the value 2 (about 9 percent too low) More formally, the signal-to-noise ratio is better for loud talkers than for quiet talkers Therefore, we use nonuniform quantization This approach involves the usage of smaller quantization steps at smaller signal levels and larger quantization steps for larger signal levels This process gives greater granularity at low signal levels and less granularity at high signal levels The effect is to spread the signal-to-noise ratio more evenly across the range of different signals and to enable fewer bits to be used compared to uniform quantization In a coder where the quantization levels are simply sent from one end to the other, this technique translates to a lower bandwidth requirement than for uniform quantization
Types of Speech Coders
Before we get into descriptions of the various types of codecs available, it is first worth looking at the various categories of codecs Three types exist: waveform codecs, source codecs (also known as vocoders), and hybrid codecs Waveform codecs basically sample and code the incoming analog signal without any thought as to how the signal was generated in the first place They then transmit quantized values of the samples to the destination end, where the original signal is reconstructed, at least to a very good approximation Generally, waveform codecs produce a high-quality output and are not very complex The big disadvantage is that they consume large amounts of bandwidth compared to other codecs When waveform coders are used at lower bandwidths, the speech quality degrades significantly
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Speech-Coding Techniques
Speech-Coding Techniques
Source codecs attempt to match the incoming signal to a mathematical model of how speech is produced They usually use a linear predictive filter model of the vocal tract, with a voiced/unvoiced flag to represent the excitation applied to the filter In other words, the filter represents the vocal tract and the voiced/unvoiced flag represents whether a voiced or unvoiced input is received from the vocal cords The information that is sent to the far end is a set of model parameters rather than a representation of the signal itself The far end, using the same modeling technique in reverse, takes the values received and reconstructs an analog signal Vocoders operate at low bit rates but tend to produce speech that sounds synthetic Using higher bit rates does not offer much improvement due to the limitations in the underlying model Although vocoders are used in private communications systems and particularly in military applications, they are generally not used in public networks Hybrid codecs attempt to provide the best of both worlds Although they attempt to perform a degree of waveform matching, they also utilize knowledge of how people produce sounds in the first place They tend to provide quite good quality at lower bit rates than waveform coders Figure 3-7 shows a comparison of the three types of codec with respect to quality and bandwidth
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