Hardware Design of Advanced Voice Separation and Enhancement System
碩士 === 國立中央大學 === 電機工程學系 === 104 === Blind source separation uses convolutive mixture signals as assumptions to reconstruct different signals. The mixture signals will go through a short time Fourier transform, and then being transferred into frequency domain. Because of the haracteristics of the si...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2016
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| Online Access: | http://ndltd.ncl.edu.tw/handle/33271044188066333703 |
| Summary: | 碩士 === 國立中央大學 === 電機工程學系 === 104 === Blind source separation uses convolutive mixture signals as assumptions to reconstruct different signals. The mixture signals will go through a short time Fourier transform, and then being transferred into frequency domain. Because of the haracteristics of the signal sources are sparse. We can gather time-frequency point by spatial characteristics. Generally speaking, we can apply various sound sources to the different phase between the two microphones and the intensity ratio as the spatial characteristics. Our system is a smart electronic system. We can apply frequency masking techniques in case of binary frequency distribution sparse signal to separate signals without knowing where the source is.
We have a complete system-level solution on algorithm and VLSI implementation. This design is using TSMC 90 nm library with 10 MHz operation frequency. Without calculating memory of gate count about 119.71K. Power consumption about 2.92mW and memory usage is 69Kbits.
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