Takashi Fukuda

Distinctive phonetic feature extraction for robust speech recognition

The paper describes an attempt to extract distinctive phonetic features (DPFs) that represent articulatory gestures in linguistic theory by using a multilayer neural network (MLN) and to apply the DPFs to noise-robust speech recognition. In the DPF extraction stage, after converting a speech signal to acoustic features composed of local features (LFs), an MLN with 33 output units, corresponding to context-dependent DPFs of 11 DPFs, 11 preceding context DPFs, and 11 following context DPFs, maps the LFs to DPFs. The proposed DPF parameters without MFCC (Mel-frequency cepstral coefficients) were firstly evaluated in comparison with a standard parameter set of MFCC and dynamic features on a word recognition task using clean speech; the result showed the same performance as that of the standard set. Noise robustness of these parameters was then tested with four types of additive noise and the proposed DPF parameters outperformed the standard set except for one additive noise type.

Pitch-synchronous ZCPA (PS-ZCPA)-based feature extraction with auditory masking

A pitch-synchronous (PS) auditory feature extraction method, based on ZCPA (zero-crossings peak-amplitudes), has been proposed (Ghulam, M. et al., Proc. ICSLP04, 2004) and was shown to be more robust than the conventional ZCPA (Kim, D.S. et al., IEEE Trans. Speech Audio Process., vol.7, no.1, p.55-69, 1999). We examine the effect of auditory masking, both simultaneous and temporal, in the PS-ZCPA method. We also observe the effect of varying the number of histogram bins on the way to find out the optimum parameters of the proposed method. Experimental results demonstrate the improved performance of the PS-ZCPA method achieved by embedding auditory masking into it; for example, with both the masking methods embedded, the performance increases to 73.71% from the 69.92% obtained without masking for PS-ZCPA, while it showed little improvement with an increased number of histogram bins.

Peripheral features for HMM-based speech recognition

This paper describes an attempt to extract peripheral features of a point c(t/sub i/,q/sub j/) on a time-quefrency (TQ) pattern by observing n/spl times/n neighborhoods of the point, and then to incorporate these peripheral features into the MFCC-based feature extractor of a speech recognition system as a replacement to dynamic features. In the design of the feature extractor, firstly, the orthogonal bases extracted directly from speech data by using the Karhunen-Loeve transform (KLT) of 7/spl times/3 blocks on a TQ pattern are adopted as the peripheral features, then, the upper two primal bases are selected and simplified in the form of /spl utri//sub t/-operator and /spl utri//sub q/-operator. The proposed feature-set of MFCC and peripheral features shows significant improvements in comparison with the standard feature-set of MFCC and dynamic features in experiments with an HMM-based automatic speech recognition (ASR) system. The reason for the increased performance is discussed in terms of minimal-pair tests.

PS-ZCPA Based Feature Extraction with Auditory Masking, Modulation Enhancement and Noise Reduction for Robust ASR

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 conditions with different signal-to-noise ratio (SNR). Next, auditory masking, a well-known auditory perception, and modulation enhancement that simulates a strong relationship between modulation spectrums and intelligibility of speech are embedded into the PS-ZCPA method. Finally, a Wiener filter based noise reduction procedure is integrated into the method to make it more noise-robust, and the performance is evaluated against ETSI ES202 (WI008), which is a standard front-end for distributed speech recognition. All the experiments were carried out on Aurora-2J database. The experimental results demonstrated improved performance of the PS-ZCPA method by embedding auditory masking into it, and a slightly improved performance by using modulation enhancement. The PS-ZCPA method with Wiener filter based noise reduction also showed better performance than ETSI ES202 (WI008).

Confidence scoring for accurate HMM-based word recognition by using SM-based monophone score normalization

In this paper, we propose a novel confidence scoring method that is applied to N-best hypotheses output from an HMM-based classifier. In the first pass of the proposed method, the HMM-based classifier with monophone models outputs N-best hypotheses and boundaries of all the monophones in the hypotheses. In the second pass, an SM(sub-space method)-based verifier tests the hypotheses by comparing confidence scores. We discuss how to convert a monophone similarity score of SM into a likelihood score, how to normalize the variations of acoustic quality in an utterance, and how to combine an HMM-based likelihood of word level and an SM-based likelihood of monophone level. In the experiments performed on speaker-independent word recognition, the proposed confidence scoring method significantly improves correct word recognition rate from 95.3% obtained by the standard HMM classifier to 98.0%.

Cancer of the mandibular gingiva metastasizing to the small intestine

Head and neck cancer metastasizing to the small intestine is very rare. Here we report a case of cancer of the mandibular gingiva metastasizing to the small intestine. The patient was an 82-year-old man who had squamous cell carcinoma of the mandibular gingiva staged as T2N2bM0. Two months after surgery, he presented with lower abdominal pain accompanied by signs of peritoneal irritation. Urgent abdominal surgery was performed, during which a crater-shaped perforation was noted on the wall of the ileum. Microscopic findings at this site confirmed a diagnosis of metastatic squamous cell carcinoma in the small intestine from the mandibular gingiva. To our knowledge, this is the first case report of oral cancer metastasizing to the small intestine. If gastrointestinal symptoms appear in a patient with advanced oral cancer, a differential diagnosis of metastasis to the gastrointestinal tract should be kept in mind.