This paper proposes a method to estimate the waveform of sound sources. This is accomplished by using a microphone array where the microphones are not situated close to the sound sources. The waveform is estimated using the sound velocity and positions of the microphones and sound sources as the only fixed parameters. The positions of the sound sources can be estimated in advance by using a conventional method such as multiple signal classification method (MUSIC). An iteration method is introduced to reduce the effect of direct sounds and of significant image sources due to reflected noise and/or other sound sources, whose positions are known. Computer simulations and an experiment with loudspeakers were conducted to demonstrate the effectiveness of our method.

For the effective reduction of noise that is suddenly switched on or transient, attenuation is required from its onset. A weighted recursive least square approach, where an extra term providing an initial directivity is combined with the power minimization term, is proposed. A noise reduction system is also proposed.>

The authors propose a phoneme recognition method based on the learning vector quantization (LVQ2) algorithm. They propose three kinds of modified training algorithms for the LVQ2 algorithm. In the recognition stage, the likelihood matrix is computed using the reference vectors and then the optimum phoneme sequence is computed from the matrix using the two-level dynamic programming (DP)-matching with duration constraints. The recognition score of phonemes in isolated spoken words was 89.1% for the test set. The phoneme recognition scores obtained by the modified LVQ2 algorithm were higher than those obtained by the original LVQ2 algorithm. The authors applied this method to a multi-speaker-dependent phoneme recognition task for continuous speech uttered Bunsetsu-by-Bunsetsu. The phoneme recognition score was 85.5% for the test speech samples in continuous speech.>

A method is described to estimate, using many sensors (microphones) both the position and the waveform of individual sound sources by decreasing the effects of other sound sources and reflection from walls and/or ceilings. Some experiments using two sound sources and 16 sensors have been carried out in a room with a reverberation time of 0.5 s, and it is found that the waveform of the specified sound source could be estimated by decreasing the effect of other sound sources by about 20 dB.>

A method of designing a digital hearing aid suitable for sensorineural hearing loss with a narrow audible range is proposed. The input signal is divided into short-time blocks (8 ms), and its spectrum is calculated using short-time fast Fourier transforms. The frequency-gain characteristic of the block is determined using the calculated spectrum and loudness compensation functions which describe the relation between the loudness perceived by normal listeners and that perceived by an impaired listener. The input signal within the block is processed by a single digital filter using the calculated gain characteristics. This algorithm is realized using a digital signal processor. The results of monosyllabic speech tests were that the scores of the speech test for the proposed system were improved over a wide range of input levels compared with those for the linear system for nine of 13 sensorineural impaired subjects.>

A method to estimate the shape of the foundation piles is described. The head of the pile is hit with a small hammer and the reflected wave is recorded with a vibration pick-up attached to the same head. The method automatically estimates the shape of the pile from the recorded wave. By computer simulations and experiments using model piles, it is confirmed that the proposed method correctly estimates the shape of the underground piles.>