Junsei Horikawa

Learn More
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 pitchsynchronous mechanism is embedded in ZCPA (ZeroCrossings Peak-Amplitudes), which has previously been shown to outperform the conventional features in the presence of noise. A(More)
A pitch-synchronous (PS) auditory feature extraction method based on ZCPA (Zero-Crossings PeakAmplitudes) was proposed in [1] and showed more robust over the conventional ZCPA [2]. In this paper, we examine the effect of auditory masking, both simultaneous and temporal, into the proposed PS-ZCPA method. We also observe the effect of varying the number of(More)
A pitch-synchronous (PS) auditory feature extraction method based on ZCPA (Zero-Crossings Peak-Amplitudes) was proposed previously and showed more robustness over a conventional ZCPA and MFCC based features. In this paper, firstly, a non-linear adaptive threshold adjustment procedure is introduced into the PS-ZCPA method to get optimal results in noisy(More)
Segmentation of speech into its corresponding phones has become very important issue in many speech processing areas such as speech recognition, speech analysis, speech synthesis, and speech database. In this paper, for accurate segmentation in speech recognition applications, we introduce Distinctive Phonetic Feature (DPF) based feature extraction using a(More)
Constructing a discrete model like a cellular automaton is a powerful method for understanding various dynamical systems. However, the relationship between the discrete model and its continuous analogue is, in general, nontrivial. As a quantum-mechanical cellular automaton, a discrete-time quantum walk is defined to include various quantum dynamical(More)
In this paper, we propose a novel pitch-synchronous auditory-based feature extraction method for robust automatic speech recognition (ASR). A pitch-synchronous zero-crossing peak-amplitude (PS-ZCPA)-based feature extraction method was proposed previously, and showed improved performance except while modulation enhancement was integrated together with Wiener(More)
A novel pitch-synchronous auditory-based feature extraction method for robust automatic speech recognition (ASR) is proposed. A pitch-synchronous zero-crossing peak-amplitude (PS-ZCPA)-based feature extraction method was proposed previously and it showed improved performances except when modulation enhancement was integrated with Wiener filter (WF)-based(More)
  • 1