Published on Apr 02, 2024
WELCOME TO THE SEMINAR
ON
A Novel Method Of Compressing Speech With Higher Bandwidth Efficiency
Introduction
==> This paper illustrates a novel method of speech compression and transmission.
==> This method saves the transmission bandwidth required for the speech signal by a considerable amount.
==> This scheme exploits the property of low pass nature of the speech signal.
==> Also this method applies equally well for any signal, which is low pass in nature, speech being the more widely used in Real Time Communication, is highlighted here
Properties of Speech Signals
==> They are low pass in nature
==> Their power spectrum approaches zero for zero frequency and reaches a peak in the neighborhood of few hundred Hertz
==> Hearing mechanism is highly sensitive to frequency
==> Frequency band from 300 to 3100 Hz is considered adequate for telephonic communication
A typical speech signal
==> Figure
Description
==> Transmitting the spectrum of the signal instead of transmitting the original signal is far more efficient.
==> This is because the energy of the speech signal above 4 kHz is negligible; we can very well compute the spectrum of the signal and transmit only the samples that correspond to 4 KHz of the spectrum irrespective of the sampling frequency
==> By this type of transmission we can save the bandwidth required for transmission considerably.
==> Also it is not necessary that we have to transmit all the samples corresponding to the 4 kHz frequencies, as it is sufficient to transmit a fraction of the samples without any degradation in the quality
Algorithm
==> Divide the speech samples into a set of packets each of size ‘N’
==> Compute the corresponding N-point DFT of each packet.
==> By signal processing, embed the phase information into the magnitude spectrum
==> Select only ‘αN’ number of samples of each packet and transmit it
==> Follow a similar reverse process at the receiver to reconstruct the signal
What do we require?
==> We expect the value of α to be very low because to achieve maximum reduction in the number of samples to be transmitted
==> We expect ‘N’ to be very low as it is an important factor in determining the speed of operation of the transmitter because at the transmitter the ‘N’ samples are fed to a processor, which computes the FFT of the samples.
==> The time required for this operation would be O[logN]
How does it work?
==> Simply speaking, the phase information is embedded with the magnitude of the frequency samples by transforming the frequency samples from complex to real one.
==> This has an added advantage because for any low pass signal the frequency spectrum obtained by this method is found to roll off very rapidly compared to the ordinary spectrum
==> Hence the total number of significant frequency samples obtained with this method is very less compared with the actual frequency spectrum samples of the signal.
==> This helps us to effectively reduce the number of samples to be chosen thereby reducing the number of samples to be transmitted
Conclusion
==> This paper illustrates a novel method of speech compression and transmission.
==> This method saves the transmission bandwidth required for the speech signal by a considerable amount.
==> This scheme exploits the property of low pass nature of the speech signal.
==> As per this method, the low pass signal (speech) at the transmitter is divided into set of packets, each containing, say N number of samples. Of the N samples per packet, only certain lesser number of samples, say N alone are transmitted
References
==> www.seminarsonly.com
==> mail : contactv2@gmail.com
| Are you interested in this topic.Then mail to us immediately to get the full report.
email :- contactv2@gmail.com |
