As music of digital form has been widely used, many people have been interested in the automatic extraction of natural information of music itself, such as key of a music, chord progression, melody progression, tempo, etc. Although some studies have been tried, consistent and reliable results of musical information extraction had not been achieved. In this paper, we propose a method to extract chord and tempo information from general polyphonic music signals. Chord can be expressed by combination of some musical notes and those notes also consist of some frequency components individually. Thus, it is necessary to analyze the frequency components included in musical signal for the extraction of chord information. In this study, we utilize a sinusoidal modeling, which uses sinusoids corresponding to frequencies of musical tones, and show reliable chord extraction results of sinusoidal modeling. We could also find that the tempo of music, which is the one of remarkable feature of music signal, interactively supports the chord extraction idea, if used together. The proposed scheme of musical feature extraction is able to be used in many application fields, such as digital music services using queries of musical features, the operation of music database, and music players mounting chord displaying function, etc.

The distortion effects of microphones have been analyzed and compensated at mel-frequency feature domain. Unlike popular bias removal algorithms a linear transformation of mel-frequency spectrum is incorporated. Although a diagonal matrix transformation is sufficient for medium-quality microphones, a full-matrix transform is required for low-quality microphones with severe nonlinearity. Proposed compensation algorithms are tested with HTIMIT database, which resulted in about 5 percents improvements in recognition rate over conventional CMS algorithm.

Both ultrasonic velocity at 3 MHz and absorption coefficient for the frequency range of 0.2-2 MHz were measured in an aqueous solution of polyacrylamide for the concentration range of 0.5% to 2.5% by weight. Pulse echo overlap method was taken for measuring the ultrasonic velocity over the temperature range of 10-90℃ and the high-Q ultrasonic resonator method was used for the absorption coefficient at 30℃. The velocity exhibited a maximum value at approximately 70℃, 71℃, 72℃, 73℃ and 74℃ in 2.5%, 2.0%, 1.5%, 1.0%, and 0.5% solutions, respectively. The velocity increased with the concentration at a given temperature. The ultrasonic absorption (a/f²) at a given temperature increased linearly with the concentration for the concentration below 1.5%, but suddenly increased for the concentration above 1.5% concentration. The value of a/f² at 1MHz was entirely due to the classical Stoke's viscous effect. The ultrasonic relaxation in polyacrylamide aqueous solutions, which may be the result of structural fluctuations of polymer molecules such as the segmental motion of the polymer chains, was observed, and at 2.5%, the value of a/f² was found to suddenly increase as frequency decreased.

We present an adaptive wavelet packet based speech enhancement method with robust voice activity detection (VAD) in non-stationary noise environment. The proposed method can be divided into two main procedures. The first procedure is a VAD with adaptive wavelet packet transform. And the other is a speech enhancement procedure based on the proposed VAD method. The proposed VAD method shows remarkable performance even in low SNRs and non-stationary noise environment. And subjective evaluation shows that the performance of the proposed speech enhancement method with wavelet bases is better than that with Fourier basis.

Shear wave velocity was measured and grain size analysis was conducted on two core samples obtained in unconsolidated marine sediments of the western continental margin, the East Sea. A pulse transmission technique based on the Hamilton frame was used to measure shear wave velocity. Duomorph ceramic bender transducer-receiver elements were used to generate and detect shear waves in sediment samples. Time delay was calculated by changing the sample length from the transducer-receiver element. Time delay is 43.18 μs and shear wave velocity (22.49 m/s) is calculated from the slope of regression line. Shear wave velocities of station 1 and 2 range from 8.9 to 19.0 m/s and from 8.8 to 22 mis, respectively. Shear wave velocities with depth in both cores are qualitatively in agreement with the compared model〔1〕, although the absolute value is different. The sediment type of two core samples is mud (mean grain size, 8-9Φ). Shear wave velocity generally increases with sediment depth, which is suggesting normally consolidated sediments. The complicated variation of velocity anisotropy with depth at station 2 is probably responsible for sediment disturbance by possible gas effect.

As the needs for wireless Internet service is increasing, the needs for secure m-commerce is also increasing. Conventional security techniques are reinforced by biometric security technique. This paper utilized the voice as biometric security techniques. We developed speaker verification system for m-commerce (mobile commerce) via wireless internet and wireless application protocol (WAP). We named this system the mVprotek. We implemented the system as client-server architecture. The clients are mobile phone simulator and personal digital assistant (PDA). The verification results are obtained by integrating the mVprotek system with SK Telecom's code dimension multiple access (CDMA) system. Utilizing f-ratio weighting and virtual cohort model normalization showed much better performance than conventional background model normalization technique.

General algorithm is developed for the prediction of internal flow-induced noise. This algorithm is based on the integral formula derived by using the General Green Function, Lighthill's acoustic analogy and Curl's extension of Lighthill's. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve are compared with actual measurements. This illustrative computation shows that the current method penn its generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.