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Precise short-frame spectrum analysis LSI based on advanced maximum entropy method

机译:基于高级最大熵方法的精确短帧频谱分析LSI

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The authors have studied the conventional MEM (maximum entropy method) and developed an MEM algorithm for a precise spectrum analysis method in short-duration frames very little affected by noise. The new algorithm requires about twice as large a word length and ten times as large a processing speed as conventional spectrum analysis algorithms, so it is implemented in the form of a dedicated LSI. This LSI is a DSP-type LSI with a 32-b*16-b multiplier, a 56-b ALU, and a barrel shifter within a chip. A speaker-independent voice recognition system featuring accurate identification of phonemes can be constructed by combining this LSI with a voice-pattern-matching LSI.
机译:作者已经研究了传统的MEM(最大熵方法),并开发了一种在短时帧中受噪声影响很小的精确频谱分析方法的MEM算法。这种新算法所需的字长约为常规频谱分析算法的两倍,而处理速度却是常规频谱分析算法的十倍,因此它以专用LSI的形式实现。该LSI是在芯片内具有32b * 16b乘法器,56b ALU和桶形移位器的DSP型LSI。通过将该LSI与语音模式匹配LSI相结合,可以构建具有准确识别音素特征的独立于说话者的语音识别系统。

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