In this paper, we propose a new technique of filter bank subtraction for robust speech recognition under various acoustic conditions. Spectral subtraction is a simple and useful technique for reducing the influence of additive noise. Conventional spectral subtraction assumes accurate estimation of the noise spectrum and no correlation between speech and noise. Those assumptions, however, are rarely satisfied in reality, leading to the degradation of speech recognition accuracy. Moreover, the recognition improvement attained by conventional methods is slight when the input SNR changes sharply. We propose a new method in which the output values of filter banks are used for noise estimation and subtraction. By estimating noise at each filter bank, instead of at each frequency point, the method alleviates the necessity for precise estimation of noise. We also take into consideration expected phase differences between the spectra of speech and noise in the subtraction and control a subtraction coefficient theoretically. Recognition experiments on test sets at several SNRs showed that the filter bank subtraction technique improved the word accuracy significantly and got better results than conventional spectral subtraction on all the test sets. In other experiments, on recognizing speech from TV news field reports with environmental noise, the proposed subtraction method yielded better results than the conventional method.

This paper describes a method for separating a target sound from other noise arriving in a single direction when the target cannot, therefore, be separated by directivity control. Microphones are arranged in a line toward the sources to form null sensitivity points at given distances from the microphones. The null points exclude non-target sound sources on the basis of weighting coefficients for microphone outputs determined by blind source separation. The separation problem is thereby simplified to instantaneous separation by adjustment of the time-delays for microphone outputs. The system uses a direct (i.e. non-iterative) algorithm for blind separation based on second-order statistics, assuming that all sources are non-stationary signals. Simulations show that the 2-microphone system can separate a target sound with separability of more than 40 dB for the 2-source problem, and 25 dB for the 3-source problem when the other sources are adjacent.

Control of the pulse collision point on an axon, prior to the propagation time measurement facilitates the detection of the non-uniformity of an axon, similar to a TDR on transmission lines. The measurement requires the placement of electrodes only on the extremities of the axon.

There is a strong demand to expand captioned broadcasting for TV news programs in Japan. However, keyboard entry of captioned manuscripts for news program cannot keep pace with the speed of speech, because in the case of Japanese it takes time to select the correct characters from among homonyms. In order to implement simultaneous subtitled broadcasting for Japanese news programs, a simultaneous subtitling system by speech recognition has been developed. This system consists of a real-time speech recognition system to handle broadcast news transcription and a recognition-error correction system that manually corrects mistakes in the recognition result with short delay time. NHK started simultaneous subtitled broadcasting for the news program "News 7" on the evening of March 27, 2000.