The paper gives the details about the speech compression using discrete wavelet transform in FPGA... more The paper gives the details about the speech compression using discrete wavelet transform in FPGA. In today's world multimedia files are used, storage space required for these files is more and sound files have no option so ultimate solution for this is compression. Compression is nothing but high input stream of data converted into smaller size. Compression is done for all, such as image, data; signals. Here speech compression technique is used and done using DWT. For this purpose only single level implementation is done to get compressed signal, and this is implemented in FPGA by using VHDL code. In this technique DWT code is written in VHDL that include separation of high level component and low level component from given input wav file and after separating these components down sampling is done and we get the compressed speech signal by keeping only approximation part of the result. The compressed speech signal was read back after up-sampling was performed. The resulting compressed signal is with some noise and future work is to reduce noise.
The paper gives the details about the speech compression using discrete wavelet transform in FPGA... more The paper gives the details about the speech compression using discrete wavelet transform in FPGA. In today's world multimedia files are used, storage space required for these files is more and sound files have no option so ultimate solution for this is compression. Compression is nothing but high input stream of data converted into smaller size. Compression is done for all, such as image, data; signals. Here speech compression technique is used and done using DWT. For this purpose only single level implementation is done to get compressed signal, and this is implemented in FPGA by using VHDL code. In this technique DWT code is written in VHDL that include separation of high level component and low level component from given input wav file and after separating these components down sampling is done and we get the compressed speech signal by keeping only approximation part of the result. The compressed speech signal was read back after up-sampling was performed. The resulting compressed signal is with some noise and future work is to reduce noise.
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