Abstract
- Speech compression plays an important role in applications which require the minimization of the storage and/or transmission requirements, such as multimedia, integrated services digital networks (ISDN), voice response systems and cellular telephony. Vector quantization (VQ) is a well-known compression technique which has been widely used in many speech coding systems. In the present work, an algorithm for designing codebooks for voice waveform vector quantization is presented. Simulations are carried out to compare the performance of the proposed algorithm, which is based on principal component analysis (PCA), to the performance of two other design approaches: the traditional LBG (Linde-Buzo-Gray) algorithm and a self-organizing neural network algorithm.
Highlights
Speech compression plays an important role in applications which require the minimization of the storage and/or transmission requirements, such as multimedia, integrated services digital networks (ISDN), voice response systems and cellular telephony
Vector quantization (VQ) has been widely used in many speech and image coding systems [1, 2], due to the theoretically proved fact that it results in a lower distortion for a given rate as compared to scalar quantization [3]
Speech coding is essential for applications such as voice messaging, multimedia, teleconferencing, integrated services di~ital networks (ISDN), voice response systems, wireless communications, digital telephone answering machines and security devices [4]
Summary
Abstract - Speech compression plays an important role in applications which require the minimization of the storage and/or transmission requirements, such as multimedia, integrated services digital networks (ISDN), voice response systems and cellular telephony. Simulations are carried out to compare the performance of the proposed algorithm, which is based on principal component analysis (PCA), to the performance of two other design approaches: the traditional LBG (Linde-Buzo-Gray) algorithm and a self-organizing neural network algorithm. Codebook design, voice waveform coding, principal component analysis, KarhunenLoeve transform. Vector quantization (VQ) has been widely used in many speech and image coding systems [1, 2], due to the theoretically proved fact that it results in a lower distortion for a given rate as compared to scalar quantization [3]. An algorithm for designing codebooks for voice waveform vector quantization is presented. It is based on Principal Component Analysis (PCA). Codebook design plays a crucial role in the scenario of signal compression systems based on vector quantization.
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