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To transmit voice from one place to another, the speech (acoustic signal) is first converted into an electrical signal using a transducer, the microphone. This electrical signal is an analog signal. The voice signal corresponding to the speech "how are you" is shown in Figure 4.1. The important characteristics of the voice signal are given here:
The voice signal occupies a bandwidth of 4kHz i.e., the highest frequency component in the voice signal is 4kHz. Though higher frequency components are present, they are not significant, so a filter is used to remove all the high-frequency
The pitch varies from person to person. Pitch is the fundamental frequency in the voice signal. In a male voice, the pitch is in the range of 50–250 Hz. In a
The speech sounds can be
Voice signal is considered a nonstationary signal, i.e., the characteristics of the signal (such as pitch and energy) vary. However, if we take small portions of the voice signals of about 20msec duration, the signal can be
Figure 4.1: Speech waveform.
The voice signal occupies a bandwidth of 4KHz. The voice signal can be broken down into a fundamental frequency and its harmonics. The fundamental frequency or pitch is low for a male voice and high for a female voice.
These characteristics are used while converting the analog voice signal into digital form. Analog-to-digital conversion of voice signals can be done using one of two techniques: waveform coding and
The characteristics of speech signals described here are used extensively for speech processing applications such as text-to-speech conversion and speech recognition.
Music signals have a bandwidth of 20kHz. The techniques used for converting music signals into digital form are the same as for voice signals.
Waveform coding is done in such a way that the analog electrical signal can be reproduced at the receiving end with minimum distortion. Hundreds of waveform coding techniques have been proposed by many researchers. We will study two important waveform coding techniques: pulse code modulation (PCM) and adaptive differential pulse code modulation (ADPCM).
Pulse Code Modulation (PCM) is the first and the most widely used waveform coding technique. The ITU-T Recommendation G.711 specifies the algorithm for coding speech in PCM format.
PCM coding technique is based on Nyquist's theorem, which states that if a signal is sampled uniformly at least at the rate of twice the highest frequency component, it can be reconstructed without any distortion. The highest frequency component in voice signal is 4kHz, so we need to sample the waveform at 8000 samples per second—every 1/8000th of a second (125 microseconds). We have to find out the amplitude of the waveform for every 125 microseconds and transmit that value instead of transmitting the analog signal as it is. The sample values are still analog values, and we can "quantize" these values into a fixed number of levels. As shown in Figure 4.2, if the number of quantization levels is 256, we can represent each sample by 8 bits. So, 1 second of voice signal can be represented by 8000 × 8 bits, 64kbits. Hence, for transmitting voice using PCM, we require 64 kbps data rate. However, note that since we are approximating the sample values through quantization, there will be a distortion in the reconstructed signal; this distortion is known as quantization noise .
Figure 4.2: Pulse Code Modulation.
ITU-T standard G.711 specifies the mechanism for coding of voice signals. The voice signal is
In the PCM coding technique standardized by ITU in the G.711 recommendation, the nonlinear characteristic of human hearing is exploited— the ear is more sensitive to the quantization noise in the lower amplitude signal than to noise in the large amplitude signal. In G.711, a
For CD-quality audio, the sampling rate is 44.1kHz (one sample every 23 microseconds), and each sample is coded with 16 bits. For two-channel stereo audio stream, the bit rate required is 2 × 44.1 × 1000 × 16 = 1.41Mbps.
The quality of speech obtained using the PCM coding technique is called toll quality. To compare the quality of different coding techniques, toll quality speech is taken as the reference.
One simple modification that can be mode to PCM is that we can code the difference between two successive samples rather than coding the samples directly. This technique is known as differential pulse code modulation (DPCM).
Another characteristic of the voice signal that can be used is that a sample value can be predicted from past sample values. At the transmitting side, we predict the sample value and find the difference between the
ITU-T Recommendation G.721 specifies the coding algorithm. In ADPCM, the value of speech sample is not transmitted, but the difference between the predicted value and the actual sample value is.
The block diagram of an ADPCM encoder is shown in Figure 4.3(a). Eight-bit [.mu]-law PCM samples are input to the encoder and are converted into linear format. Each sample value is predicted using a prediction algorithm, and then the predicted value of the linear sample is subtracted from the actual value to generate the difference signal. Adaptive quantization is performed on this difference value to produce a 4-bit ADPCM sample value, which is transmitted. Instead of representing each sample by 8 bits, in ADPCM only 4 bits are used. At the receiving end, the decoder, shown in Figure 4.3(b), obtains the dequantized version of the digital signal. This value is added to the value generated by the adaptive
Figure 4.3: (a) ADPCM Encoder.
Figure 4.3: (b) ADPCM Decoder.
There are many waveform coding techniques such as delta modulation (DM) and continuously variable slope delta modulation (CVSD). Using these, the coding rate can be reduced to 16kbps, 9.8kbps, and so on. As the coding rate
The PCM coding technique is used extensively in telephone networks. ADPCM is used in telephone networks as well as in many radio systems such as digital enhanced cordless telecommunications (DECT).
In ADPCM, each sample is represented by 4 bits, and hence the data rate required is 32kbps. ADPCM is used in telephone networks as well as radio systems such as DECT.
Over the past 50
Figure 4.4: Electrical model of speech production.
In vocoding techniques, at the transmitter, the speech signal is divided into frames of 20msec in duration. Each frame contains 160 samples. Each frame is
In vocoding techniques, the electrical model of speech production is used. In this model, the vocal tract is represented as a filter. The filter is excited by a pulse generator to produce voiced sounds and by a noise generator to produce unvoiced sounds.
The voice generated using the vocoding techniques sounds very mechanical or robotic. Such a voice is called
The basic concept of linear prediction is that the sample of a voice signal can be approximated as a linear combination of the past samples of the signal.
If S n is the n th speech sample, then
(k = 1,
,P) are the linear prediction coefficients, G is the gain of the vocal tract filter, and U
is the excitation to the filter. Linear prediction coefficients (generally 8 to 12) represent the vocal tract filter coefficients. Calculating the linear prediction coefficients involves solving P linear equations. One of the most widely used
Coding of the voice signal using linear prediction analysis involves the following steps:
At the transmitting end, divide the voice signal into frames, each frame of 20msec duration. For each frame, calculate the linear prediction coefficients and pitch and find out whether the frame is voiced or unvoiced. Convert these values into code words and send them to the receiving end.
At the receiver, using these parameters and the speech production model, reconstruct the voice signal.
In linear prediction technique, a voice sample is approximated as a linear combination of the past n samples. The linear prediction coefficients are calculated every 20
Using linear prediction vocoder, voice signals can be compressed to as low as 1.2kbps. Quality of speech will be very good for data rates down to 9.6kbps, but the voice sounds synthetic for further lower data rates. Slight variations of this technique are used extensively in many practical systems such as mobile communication systems, speech synthesizers, etc.
Variations of LPC technique are used in many commercial systems, such as mobile communication systems and Internet telephony.
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