A noise-robust feature extraction method based on pitch-synchronous ZCPA for ASR

Ghulam Muhammad, Takashi Fukuda, Junsei Horikawa, Tsuneo Nitta

In this paper, we propose a novel feature extraction method based on an auditory nervous system for robust automatic speech recognition (ASR). In the proposed method, a pitch-synchronous mechanism is embedded in ZCPA (Zero-Crossings Peak-Amplitudes), which has previously been shown to outperform the conventional features in the presence of noise. A noise-robust non-delayed pitch determination algorithm (PDA) is also developed. In the experiment, the proposed pitch-synchronous ZCPA (PS-ZCPA)was proved more robust than the original ZCPA method. Moreover, a simple noise subtraction (NS) method is also integrated in the proposed method and the performance was evaluated using the Aurora-2J database. The experimental results showed the superiority of the proposed PSZCPA method with NS over the PS-ZCPA method without NS.

doi: 10.21437/Interspeech.2004-101

Cite as: Muhammad, G., Fukuda, T., Horikawa, J., Nitta, T. (2004) A noise-robust feature extraction method based on pitch-synchronous ZCPA for ASR. Proc. Interspeech 2004, 133-136, doi: 10.21437/Interspeech.2004-101

@inproceedings{muhammad04_interspeech,
  author={Ghulam Muhammad and Takashi Fukuda and Junsei Horikawa and Tsuneo Nitta},
  title={{A noise-robust feature extraction method based on pitch-synchronous ZCPA for ASR}},
  year=2004,
  booktitle={Proc. Interspeech 2004},
  pages={133--136},
  doi={10.21437/Interspeech.2004-101}
}