The music game is one of the popular game styles where a player is typically requested to take specific actions at specific moments corresponding to the prominent acoustic epoch in the music playing in the background. Stage data for such games record a sequence of actions the player has to take. Creating such data is a difficult task that requires skilled artists. It is also time-consuming because such games require multiple sequences with different difficulty levels. We propose a method for generating sparse stage data with lower difficulty levels by expressing the position of the target by a certain representation of rhythm.

In extremely shallow water, such as bays and inlets, active sonar may not work sufficiently well to detect underwater threats owing to multiple reflections and strong reverberations at the sea surface and seafloor. In this study, we developed "gate sonar" on the basis of a unique method of detecting changes in the pulse signal propagated between a pair of omnidirectional transducers in a surveyed area when a target passes between the transducers. To detect changes in the received signal, we employed a time-reversed pulse as the source signal for the gate sonar; this pulse can be created even from a pair of transducers by using a virtual array formed owing to reflections at the surface and bottom boundaries. As a result of experiments in a 25 m-long swimming pool, we confirmed that the gate sonar can recognize the changes in the received signal and functions as designed. Furthermore, by applying convolutional neural network (CNN) to the received signal waveform and its spectrogram as input images, we demonstrated that the proposed time reversal mirror (TRM)-based gate sonar can improve the detection of targets, with the spectrogram performing slightly better.

When distinguishing stop consonants, Korean listeners use the fundamental frequency of the following vowel (F0) as well as the voice onset time (VOT). However, it is unclear whether the F0 and VOT of natural speech sounds play an effective role in hearing nonnative stops. In the present study, we examined whether Korean listeners perceive Japanese voiced stops, rather than Japanese voiceless stops, as being similar to Korean lenis stops depending on F0 and VOT. Native Korean listeners matched a speech sound starting with either a Japanese voiced or voiceless stop to a target. The targets were meaningful visual words starting with a lenis stop in Experiment 1 and meaningless speech sounds starting with a lenis stop in Experiment 2. Native Japanese listeners, who primarily use VOT for stop distinction, also participated in Experiment 2. The results revealed that the extent to which Korean listeners chose voiced stops was influenced consistently by F0, and the pattern of results differed between Korean and Japanese listeners. These findings suggest that even when hearing natural speech sounds, Korean listeners use F0 when judging the similarity between lenis and nonnative stops.

Time-to-contact estimation is essential for individuals to avoid collision with externally moving objects. Although the auditory system plays an important role in detecting events from all directions around listeners including events out of sight, it is still unclear how the auditory system contributes to the time-to-contact judgment. The present study investigated whether the auditory time-to-contact changed depending on the direction of the approaching sound (0°, 45°, 90°, 135°, or 180°). The results demonstrated that auditory time-to-contact judgments were underestimated compared to actual auditory time-to-contact for all directions, thus replicating the classical time-to-contact underestimation effect. In contrast, the trends observed for the auditory time-to-contact judgment for a sound stimulus approaching from behind differed from those approaching from the front, even though the auditory distance localization performance did not differ for the different angles. This difference in estimation between the sound approaching from the rear and other directions could be attributed to the sound coming from behind being more emotionally negative than the sound coming from the front.

Estimating the formant frequencies of high-pitched speech is essential in many speech processing applications. Unfortunately, most existing methods cannot accurately estimate the formant frequencies from high-pitched speech. Moreover, the available formant estimators do not show noise immunity. In this paper, we propose a higher-order group delay (GD) spectrum-based deconvolution method for formant estimation of high-pitched noisy speech with higher accuracy. Although cepstrum is known to provide a source-filter separation, to some extent, it gets affected by ambient noise. We employ the spectral-root-deconvolution technique on the third-order GD spectrum that yields a noise-robust cepstrum. The resulting cepstrum is found to produce significant improvement when estimating formant frequencies. We evaluated the proposed method on five synthetic vowels and some natural vowels spoken by male and female speakers by calculating the estimation error of the formant frequencies and standard F2–F1 plots, respectively. An utterance from the Texas Instruments and Massachusetts Institute of Technology (TIMIT) database has been utilized to plot the formant contours on the respective spectrogram. We compared the results with the three state-of-the-art methods. Our proposed technique outperforms all approaches, particularly with high-pitched speaking in a noisy environment.

Advantage of object-based audio (OBA) is that customization of the reproduced sound by individual listeners is allowed. To design the broadcasting system and transmission line for OBA, bit rate estimation of OBA program is essential; thus, how much bit rate is required for mono audio object is critical information. The bit rate required for mono audio object in OBA program compressed with MPEG-H 3D Audio is investigated using 12 mono test materials in terms of whether the broadcast quality is met. The obtained results are statistically analyzed and the bit rate meeting the broadcast quality and the bit rate of the detection limit for each mono test material is derived.

This paper reports on the implementation of a moving sound source and receiver with directivity in the two-dimensional finite-difference time-domain (FDTD) method. A two-dimensional fundamental solution of a moving monopole source is theoretically derived. Then, a fundamental solution of a moving dipole source is obtained by differentiating the fundamental solution of a monopole source in space. Finally, the directivity of moving monopole, dipole, and cardioid sources is theoretically derived. Numerical experiments performed on the two-dimensional sound field showed that the effect of moving velocity on amplitude differs for the monopole and dipole sources. Furthermore, it was found that directivity characteristics of dipole and cardioid sources vary depending on the beam steering angle and moving direction. The present method can be accurately applied to the moving sound source and receiver with directivity.

Corridors have a crucial effect on classroom acoustics, but its study is generally ignored. After examining the acoustic performance of a coupled space comprising a corridor and two classrooms, a new method for calculating the signal-to-noise ratio (SNR) by the analysis of the energy distribution is proposed in this paper. Numerical experiments are conducted using the finite element software COMSOL Multiphysics. Various parameters are explored using the proposed numerical model to determine their effect on the SNR at different receiving points in a classroom. It was observed that factors such as the corridor width, absorption of the corridor carpet materials, and aperture area (i.e., classroom doors) affect room acoustics. The results show that an absorption treatment of the corridor has a significant effect on classroom acoustic performance. The findings of this study help us understand various metrics of acoustic performance in extended coupled spaces, such as speech intelligibility in classrooms and offices.

Examples of poor heavy-weight floor impact sound performance of pure framed structures with reinforced concrete were observed relative to the floor slab thickness. To investigate the cause of the poor performance, the floor vibration characteristics of several examples of actual pure framed structures were measured during heavy-weight impact. As a result, the floor vibration characteristics of the displacement of the girders and coupled vibration of the girders and floor slabs not seen in conventional floor structures surrounded by girders with reinforced concrete walls were observed. The propagation of the vibration of the floor slab was observed in more than the range surrounded by girders and in the next slab beyond the girders owing to the vibration of the girder itself. That these physical phenomena can be evaluated using a numerical calculation method was confirmed, and the vibration of the girder itself and the actual vibration range when the floor slab is subjected to heavy-weight impact must be considered to accurately predict the heavy-weight floor impact sound performance.

We have developed an aircraft model identification system that uses a convolutional neural network (CNN). Our previous study used the CNN model to classify seven and eighteen models of jet aircraft by using training based on measured data taken directly under their flight paths near airports, reaching an accuracy of 98%. However, there were some limitations, such as the study results being obtained at only three sites, the measurements being taken only directly under the flight path, and the season being limited to winter. In this study, we examine if this method is also effective for identifying sound sources over a wider area not directly under the flight path. We conducted aircraft type identification by using the frequency characteristics of aircraft noise obtained at 90 measurement sites located within an area of approximately 30 km north-south and 6 km east-west, in summer and winter. We were able to achieve an identification rate of 98% for four types of sound sources. The results suggest that this system can identify measurement data over a wider area around airfields and can be applied to more practical issues, such as generating noise maps and validating predictions in the noise maps.