This paper proposes a new phase feature derived from the formant instantaneous characteristics for speech recognition （SR） and speaker identification （SI） systems. Using Hilbert transform （HT）, the formant chara...This paper proposes a new phase feature derived from the formant instantaneous characteristics for speech recognition （SR） and speaker identification （SI） systems. Using Hilbert transform （HT）, the formant characteristics can be represented by instantaneous frequency （IF） and instantaneous bandwidth, namely formant instantaneous characteristics （FIC）. In order to explore the importance of FIC both in SR and SI, this paper proposes different features from FIC used for SR and SI systems. When combing these new features with conventional parameters, higher identification rate can be achieved than that of using Mel-frequency cepstral coefficients （MFCC） parameters only. The experiment results show that the new features are effective characteristic parameters and can be treated as the compensation of conventional parameters for SR and SI.展开更多
基于平均法导出了Van der Pol-Duffing类振子响应时程瞬时特性与系统参数间的函数关系,在此基础上提出一种高效的非线性系统参数识别方法。借助经验包络法EE(Empirical Envelope Method)求解了响应时程瞬时特性,验证了EE相对传统Hilber...基于平均法导出了Van der Pol-Duffing类振子响应时程瞬时特性与系统参数间的函数关系,在此基础上提出一种高效的非线性系统参数识别方法。借助经验包络法EE(Empirical Envelope Method)求解了响应时程瞬时特性,验证了EE相对传统Hilbert变换HT(Hilbert Transform)方法在求解瞬时频率上的优势。通过数值算例验证了本文方法的识别精度。分析了信号长度、初始条件、采样频率和噪声比例四种因素对识别精度的影响。结果表明,线性参数识别精度不受上述因素影响,非线性刚度项系数识别精度受各因素影响较为明显;本文方法具有良好的抗噪声性能,即使系统响应受到10%的噪声污染,本文方法也具有很好的识别精度。展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No.60903186)the Shanghai Leading Academic Discipline Project (Grant No.J50104)
文摘This paper proposes a new phase feature derived from the formant instantaneous characteristics for speech recognition （SR） and speaker identification （SI） systems. Using Hilbert transform （HT）, the formant characteristics can be represented by instantaneous frequency （IF） and instantaneous bandwidth, namely formant instantaneous characteristics （FIC）. In order to explore the importance of FIC both in SR and SI, this paper proposes different features from FIC used for SR and SI systems. When combing these new features with conventional parameters, higher identification rate can be achieved than that of using Mel-frequency cepstral coefficients （MFCC） parameters only. The experiment results show that the new features are effective characteristic parameters and can be treated as the compensation of conventional parameters for SR and SI.
