Eyad Ibrahim - Profile on Academia.edu (original) (raw)

Address: Hashemite Kingdom of Jordan

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Speech coding deals with the problem of reducing the bit rate required for representing speech si... more Speech coding deals with the problem of reducing the bit rate required for representing speech signals while preserving the quality of the speech reconstructed from that representation. In this paper, we propose a novel speech coding technique, not only to compress speech signal at low bit rate, but also to maintain its quality even if the received signal is corrupted by noise. The encoder of the proposed technique is based on speech analysis/synthesis model using a sinusoidal representation where the sinusoidal components are involved to form a nearly resemblance of the original speech waveform. In the proposed technique, the original frame is divided to voiced or unvoiced sub-frames based on their energies. The aim of the division and classification is to choose the best parameters that reduce the total bit rate and enable the receiver to recover the speech signal with a good quality. The parameters involved in the analysis stage are extracted from the short-time Fourier transform where the original speech signal is converted into frequency domain. Making use of the peak-picking technique, amplitudes of the selected peaks with their associated frequencies and phases of the original speech signal are extracted. In the next stage, novel parameter reduction and quantization techniques are performed to reduce the bit rate while preserving the quality of the recovered signal.

Speech coding deals with the problem of reducing the bit rate required for representing speech si... more Speech coding deals with the problem of reducing the bit rate required for representing speech signals while preserving the quality of the speech reconstructed from that representation. In this paper, we propose a novel speech coding technique, not only to compress speech signal at low bit rate, but also to maintain its quality even if the received signal is corrupted by noise. The encoder of the proposed technique is based on speech analysis/synthesis model using a sinusoidal representation where the sinusoidal components are involved to form a nearly resemblance of the original speech waveform. In the proposed technique, the original frame is divided to voiced or unvoiced sub-frames based on their energies. The aim of the division and classification is to choose the best parameters that reduce the total bit rate and enable the receiver to recover the speech signal with a good quality. The parameters involved in the analysis stage are extracted from the short-time Fourier transform where the original speech signal is converted into frequency domain. Making use of the peak-picking technique, amplitudes of the selected peaks with their associated frequencies and phases of the original speech signal are extracted. In the next stage, novel parameter reduction and quantization techniques are performed to reduce the bit rate while preserving the quality of the recovered signal.

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