This set of Wireless & Mobile Communications Multiple Choice Questions & Answers (MCQs) focuses on “Characteristics of Speech Signals”.
1. The higher the bit rate, the more speech channels can be compressed within a given bandwidth.
a) True
b) False
View Answer
Explanation: The lower the bit rate at which the coder can deliver toll quality speech, the more speech channels can be compressed within a given bandwidth. Thus, manufacturers are continuously in search of speech coders that provide toll quality speech at lower bit rates.
2. Which of the following are two types of speech coders?
a) Waveform coders and source coders
b) Active coders and passive coders
c) Direst coders and indirect coders
d) Time and frequency coders
View Answer
Explanation: Speech coders can be categorised into waveform coders and source coders. Waveform coders can further be categorised into time domain and frequency domain. Source coders can be classified into linear predictive coders and vocoders.
3. Waveform coders has _______ complexity and achieves _______ economy in transmission bit rate.
a) Maximum, moderate
b) Maximum, high
c) Minimal, moderate
d) Minimal, high
View Answer
Explanation: Waveform coders have minimal complexity. This class of coders achieves only moderate economy in transmission bit rate. They are designed to be source independent and hence code equally well a variety of signals.
4. Vocoders has _______ complexity and achieves _______ economy in transmission bit rate.
a) Maximum, moderate
b) Maximum, high
c) Minimal, moderate
d) Minimal, high
View Answer
Explanation: Vocoders achieve very high economy in transmission bit rate. They are in general more complex. They are based on using a priori knowledge about the signal to be coded, and for this reason, they are signal specific.
5. Which of the following is not a property that is utilized in coder design?
a) Non zero autocorrelation between successive speech signals
b) Non flat nature of speech signal
c) Quasiperiodicity of voiced speech signals
d) Uniform probability distribution of speech amplitude
View Answer
Explanation: Speech waveforms have a number of useful properties that can be exploited when designing efficient coders. They are non uniform probability distribution of speech amplitude, non-zero autocorrelation between successive speech samples, the nonflat nature of the speech spectra and quasiperiodicity of voiced speech signals.
6. Speech waveforms are _______
a) Bandlimited
b) Bandpass
c) High pass
d) Infinite bandwidth
View Answer
Explanation: The most basic property of speech waveforms that are exploited by all speech coders is that they are bandlimited. A finite bandwidth means that it can be time-discretized at a finite rate and reconstructed complexity from its samples.
7. Which of the following is not a property of pdf of speech signals?
a) Non uniformity
b) Very high probability of non-zero amplitudes
c) Significant probability of very high amplitudes
d) Increasing function of amplitudes between these extremes
View Answer
Explanation: There is a non-uniform probability distribution of speech amplitude. The pdf of a speech signal is in general characterized by a very high probability of non-zero amplitudes, a significant probability of very high amplitudes, and a monotonically decreasing function of amplitudes between these extremes.
8. Auto correlation function measures______ between samples of a speech signal as a function of _______
a) Similarity, frequency
b) Dissimilarity, time
c) Similarity, time
d) Dissimilarity, frequency
View Answer
Explanation: The autocorrelation function (ACF) gives a quantitative measure of the closeness or similarity between samples of a speech signal as a function of their time separation. In every sample of speech, there is a large component that is easily predicted from the values of the previous samples.
9. Power spectral density of speech is flat.
a) True
b) False
View Answer
Explanation: There is a nonflat characteristic in power spectral density of speech. It makes it possible to obtain significant compression by coding speech in the frequency domain.
10. Spectral flatness measure is the ratio of ______ and _____
a) Variance, Geometric mean
b) Geometric Mean, Variance
c) Arithmetic mean, geometric mean
d) Geometric mean, arithmetic mean
View Answer
Explanation: Spectral flatness measure is defined as ratio of arithmetic to geometric mean of the samples of the PSD taken at uniform intervals in frequency. Spectral flatness measure is a qualitative measure of the theoretical maximum coding gain that can be obtained by exploiting the nonflat characteristics of speech spectra.
11. Low frequency signals contribute very little to the total speech signals.
a) True
b) False
View Answer
Explanation: Lon term averaged PSD’s of speech show that high frequency signals contribute very little to the total speech energy. However, high frequency components are insignificant in energy, they are very important carriers of speech information.
Sanfoundry Global Education & Learning Series – Wireless & Mobile Communications.
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