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Questions and Answers

What characterizes lossless predictive coding?

It includes a quantization step.

It employs a uniform quantizer for all signals.

The decoder produces the same signal as the original. (correct)

The decoder produces a signal that differs from the original.

In the example provided, which value is used as the initial uncoded transmission?

f5 = 22

f0 = 21 (correct)

f2 = 22

f3 = 27

How does differential PCM differ from predictive coding?

It incorporates a quantization step. (correct)

It focuses exclusively on error correction.

It does not utilize a quantizer step.

It operates without any predictor.

Which component is NOT part of a DPCM coder?

Encoder Signup and view all the answers

What does the distortion formula represent in the context of predictive coding?

The average squared error between original and reconstructed signals. Signup and view all the answers

What is one key feature of ADPCM?

It allows adaptation of the coder based on signal input. Signup and view all the answers

What role does the quantizer play in Differential PCM?

It adjusts the signal representation based on predetermined boundaries. Signup and view all the answers

What does a forward adaptive quantization approach leverage?

The characteristics of the input signal. Signup and view all the answers

What compression ratio can voice achieve as mentioned?

Which statement best describes the relationship between probability and information?

Higher probability means less information. Signup and view all the answers

Who is credited with the development of the famous Information Theory?

C.E. Shannon Signup and view all the answers

What does the logarithmic measure of information relate to?

The probability of an event occurring. Signup and view all the answers

What is the purpose of advanced compression algorithms in multimedia?

To enable them to become killer applications over networks. Signup and view all the answers

When is it impossible to compress an information source?

When it is below its entropy. Signup and view all the answers

According to the principles of Information Theory, which scenario has more information?

There will be an earthquake tonight. Signup and view all the answers

What can be concluded about the entropy of an information source?

It corresponds to the number of bits needed for encoding. Signup and view all the answers

What is the minimum required sampling rate according to the Nyquist theorem?

At least twice the maximum frequency Signup and view all the answers

What happens if the sampling rate is equal to the actual frequency of a sound signal?

A constant signal with zero frequency is detected Signup and view all the answers

Which of the following best defines quantization in the context of audio data?

The representation of amplitudes by a specific value or step Signup and view all the answers

What is the Nyquist frequency?

Half of the Nyquist rate Signup and view all the answers

What kind of noise is introduced through the process of quantization?

Quantization noise Signup and view all the answers

According to the Nyquist theorem, which of the following is true about a band-limited signal?

Sampling rate should be at least twice the range of frequency components Signup and view all the answers

What is a potential consequence of quantizing audio data?

Loss of information due to rounding Signup and view all the answers

How can incorrect sampling rates affect audio playback?

They can produce misleading frequency representations Signup and view all the answers

What is a key property of Huffman coding that prevents ambiguity in decoding?

Unique Prefix Property Signup and view all the answers

How does Huffman coding assign code lengths to symbols?

More frequent symbols have shorter codes Signup and view all the answers

What type of algorithm is the Lempel-Ziv-Welch (LZW) algorithm classified as?

A dictionary-based compression technique Signup and view all the answers

In LZW coding, what happens when the dictionary reaches its maximum size?

The code length incrementally increases Signup and view all the answers

What is the average code length for an information source S in Huffman coding relative to entropy?

Less than entropy plus one Signup and view all the answers

What is the main function of the dictionary in LZW coding?

To represent variable-length strings of symbols Signup and view all the answers

Which of the following applications commonly uses the LZW algorithm?

GIF for images Signup and view all the answers

In the context of Huffman coding, what is meant by 'optimality'?

It achieves minimum redundancy for a given probability distribution Signup and view all the answers

What is the primary purpose of backward adaptive quantization?

To reduce the impact of quantized errors Signup and view all the answers

What term describes the adaptation of predictor coefficients in predictive coding?

Adaptive Predictive Coding Signup and view all the answers

Which of the following best describes the difficulties encountered when changing prediction coefficients in a quantizer?

It creates overly complicated least-squares problems Signup and view all the answers

In adaptive predictive coding, what does M represent?

The order of the predictor based on previous values Signup and view all the answers

How does the least-squares approach relate to solving for optimal predictor coefficients?

It simplifies the problem by not using quantization errors Signup and view all the answers

What distinguishes lossless compression from lossy compression?

Lossless compression maintains original data without any loss Signup and view all the answers

Which of the following statements about quantization is accurate?

Quantization errors can necessitate changes in the quantizer Signup and view all the answers

What is implied by the term 'order' in the context of a predictor?

It indicates how many previous values are considered Signup and view all the answers

What is the main result of quantization in lossy compression?

Reduction in the number of distinct output values Signup and view all the answers

What does the Signal-to-Quantization-Noise Ratio (SQNR) formula represent?

The ratio of signal power to quantization noise power Signup and view all the answers

How does increasing the number of bits in a quantizer affect the SQNR?

It increases SQNR by 6.02 dB Signup and view all the answers

What is a characteristic feature of vector quantization compared to scalar quantization?

It concatenates consecutive samples into a single vector Signup and view all the answers

Why might the decoder of vector quantization execute quickly?

It uses pre-calculated code vectors from a codebook Signup and view all the answers

What is the primary rationale behind transform coding?

To reduce correlation between components for efficient coding Signup and view all the answers

What is a disadvantage of using vector quantization in multimedia applications?

Higher computational resources needed for encoding Signup and view all the answers

What type of quantization would use a companded quantizer?

Non-uniform quantization Signup and view all the answers

Study Notes

Multimedia Networking - Digital Audio

Sound is a wave phenomenon akin to light, but macroscopic, involving air molecule compression and expansion due to a physical device (e.g., a speaker).
Sound, as a pressure wave, has continuous values, unlike digital representations.
Sound waves exhibit ordinary wave behaviors such as reflection, refraction, and diffraction.
Digitization converts audio waves into a stream of numbers, ideally integers, for efficiency.

Digitization

An analog signal is a continuous measurement of a pressure wave.
Digitization requires sampling in both time and amplitude.
Sampling measures a quantity at evenly spaced intervals.
Sampling frequency determines the rate of sampling (e.g., 8 kHz to 48 kHz for audio).
Quantization is sampling in the amplitude dimension.
Quantization involves representing amplitudes by certain values (steps), and rounding introduces inexactness (quantization noise).

Nyquist Theorem

The Nyquist theorem dictates the sampling frequency required to reproduce the original sound accurately, ideally at least twice the maximum frequency in the signal (Nyquist rate).
A sampling rate equal to the actual frequency results in a false signal (a constant with zero frequency).
Sampling at 1.5 times the actual frequency yields an incorrect frequency (aliased frequency) lower than the correct one, with a doubled wavelength.
If a signal is band-limited (with a lower and upper frequency limit), the sampling rate must be at least twice the highest frequency component (Nyquist rate = 2 * fmax).
Nyquist frequency is half the Nyquist rate.

Signal-to-Quantization Noise Ratio (SQNR)

Quantization noise results from the conversion of continuous values into discrete values.
SQNR quantifies the quality of quantization, defined as the signal power to the quantization noise power (in decibels).

Signal-to-Noise Ratio (SNR)

SNR measures the signal quality by comparing the power of the correct signal and noise.
Measured in decibels (dB): 1 dB is a tenth of a bel.
Defined using base-10 logarithms of squared voltages (SNR = 20 log₁₀(Vsignal / Vnoise).
This is proportional to the square of the voltage. For example, if signal voltage is 10x noise, then SNR = 20 dB.

Linear vs. Non-linear Quantization

Linear format stores samples as uniformly quantized values.
Non-uniform quantization sets up more finely-spaced levels where human hearing acuity is highest.
Weber's Law states that equally perceived differences in response have values proportional to the absolute levels of the stimulus.
Non-linear quantization transforms an analog signal from the raw space to a theoretical space and uniformly quantizes the results.

Audio Quality vs. Data Rate

Uncompressed data rate increases with more bits used for quantization, and stereo doubles the bandwidth.
Examples of audio qualities and their corresponding parameters are given in a table (e.g., telephone quality, CD quality).

Coding of Audio

Involves quantization and transformation of data.
Temporal redundancy in audio exploits the differences between consecutive signals (reducing size of values) to enable more likely values using shorter bit lengths.
PCM (Pulse Code Modulation) is a general term for a process involving producing quantized sampled output, with variations such as DPCM (differences), DM (crude, efficient), and ADPCM (adaptive variant).

Pulse Code Modulation (PCM)

Given a bandwidth for speech (50 Hz to 10 kHz), the Nyquist rate dictates a sampling rate of 20 kHz.
With 8 bits per sample, the bit rate for mono speech is 160 kbps.
Standard telephony uses a bit rate of 64 kbps, considering speech signal max frequency of 4 kHz. High/low frequencies are removed using band-limiting filters.

Differential Coding of Audio

Stored as differences in simple PCM, using fewer bits. This can assign short codes to common differences and long codes to infrequent ones.

Lossless Predictive Coding

Predictive coding transmits differences between successive samples instead of samples themselves.
Predicting the next sample as equal to the current sample. The error (difference) is transmitted.
Some function of previous values can be used to gain a better prediction.
Linear predictor function is typically employed.

Differential PCM (DPCM)

DPCM is similar to predictive coding but now includes a quantizer step.

Distortion

Distortion is the average squared error between predicted and actual signal values.
D = (1/N) Σ(fn - ˜fn)²

Adaptive DPCM (ADPCM)

ADPCM adapts the coder to better suit input signals, changing step size and decision boundaries.
Adapts the predictor and quantizer. Methods exist employing forward and backward adaptive quantization.

Vocoders

Algorithms for speech synthesis using limited bit-rates.
Techniques such as using a modal speech waveform in time (LPC) or breaking down into frequency components (channel vocoder/formant vocoder) exist, for modelling salient or important frequencies.
Not as good of a simulation for natural speech.

Phase Insensitivity in Speech

Perceptual quality of speech doesn't depend on precise phase reconstruction of the waveforms, rather the amount of energy produced. Examples are shown.

Channel Vocoder

Operates at low bit-rates (1-2 kbps), by filtering the signal into frequency components and determining their power levels, analyzing pitch, and using excitation (voiced or unvoiced). Diagram is included for reference.

Formant Vocoder

Recognizes and encodes the important peaks (formants) in speech signals to produce understandable audio at low bit-rates (1 k bps) .

Linear Predictive Coding (LPC)

Extract salient features of speech directly from the waveform and uses a time-varying model to produce speech (using equations to find the vocal tract coefficients);
LPC features include speech parameter transmissions, not actual signals using small bit rates.

LPC Coding Process

Process involves determining whether the segment is voiced or unvoiced to select the generator type (wideband-noise or pulse train).

Code Excited Linear Prediction (CELP)

Attempts to improve on LPC by using a codebook of excitation vectors. More complex than LPC, providing similar audio quality at higher bitrates.

Algebraic Code Excited Prediction (ACELP)

Distributes pulses as excitation for the linear prediction filter, allowing for large codebooks and reducing processing/storage needs.
Using for different G series standard applications.

Adaptive Multi-Rate (AMR)

Speech coding optimized for link conditions and offers several bit rates.
Using discontinued transmission, voice activity detection, and comfort noise generation to reduce bandwidth use during silence periods.
Sampling frequency and bit rates described.

Voice Activity Detection (VAD)

Algorithm for speech detection from audio samples, used in speech coding and recognition.
Can determine whether speech is present or absent, and if present, whether voiced or unvoiced.

Discontinuous Transmission (DTX)

Momentarily powers down or muting mobile devices during pauses in speech transmission.
The usage of this technique conserves battery life, eases on components, and reduces interference.

Comfort Noise

Artificial background noise added to fill silences resulted from the voice activity detection.
Prevents the other end from assuming a cut transmission, based on volume levels.

Adaptive Multi-Rate - Wideband (AMR-WB)

Built on adaptive multi-rate technology (AMR).
Utilizes various bit rates.

Cisco VoIP Implementations

VoIP network benefits - e.g., efficient bandwidth use, lower transmission costs, improved employee productivity.
Describes different VoIP network components (MCU, Application Servers, call agents) and describes their interactions.
Analog to IP network conversion necessary for legacy systems.

Lossless and Lossy Compression

Lossless methods produce identical output; lossy methods do produce an approximation to the original.
Quantization is a main source of loss.

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Test your knowledge on the concepts of information theory and predictive coding, including key features like lossless predictive coding, differential PCM, and ADPCM. Answer questions about the fundamental principles that govern compression algorithms and the relationship between probability and information.

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