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The Implementation of Continuous Speech Recognition System Based on LabVIEW

机译:基于LabVIEW的连续语音识别系统的实现

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Based on software of LABVIEW, the original sound signal was usually obtained by soundcard. The process to get clean sound signal was pre-emphasis, wavelet de-noising, adding window and port detection. Continuous speech recognition system was realized by VQ (Vector Quantization) and HMM (Hidden Markov Model) for training and recognition. The Mel frequency cepstrum coefficient and its difference were used as speech recognition characteristic parameter, and ameliorative Viterbi-Beam recognition algorithm is used in the system. Experimental data indicates that ameliorative Viterbi-Beam recognition algorithm decreased the calculation of the system and also enhanced its running speed. Furthermore, the successful rate of speech recognition is about 90%, and the whole system can reach the factual applied request.
机译:基于LabVIEW的软件,原始声音信号通常由声卡获得。获得清洁声音信号的过程是预加重,小波去噪,添加窗口和端口检测。通过VQ(矢量量化)和HMM(隐马尔可夫模型)实现连续语音识别系统,用于培训和识别。 MEL频率谱系数及其差异用作语音识别特性参数,并且在系统中使用改进的维特比识别算法。实验数据表明改进的维特比识别算法降低了系统的计算,并增强了其运行速度。此外,成功的语音识别率约为90%,整个系统可以达到事实应用请求。

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