This paper overviews neural target sound information extraction (TSIE), which consists of extracting the desired information about a sound source in an observed sound mixture given clues about the target source. TSIE is a general framework, which covers various applications, such as target speech/sound extraction (TSE), personalized voice activity detection (PVAD), target speaker automatic speech recognition (TS-ASR), etc. We formalize the ideas of TSIE and show how it can be implemented through various examples such as TSE, PVAD, and TS-ASR. We conclude the paper with a discussion of potential future research directions.

We surveyed to explore how Japanese cochlear implant users perceive and enjoy music, as well as factors related to their music enjoyment. The survey gathered responses from 102 participants, showing that many continue to enjoy music after getting the implant and are keen on enjoying it even more. A time series analysis revealed that enjoyment of music decreased with hearing level, but after implantation, it improved to the same level as before the hearing loss. Additionally, there was a tendency for lower ratings of sound quality and music listening with increasing age, but participants with musical experience perceived music better than those without it. The study also suggested that practicing listening to music with cochlear implants may improve music perception. However, there were significant individual differences in the results. Especially after implantation, some people enjoyed music, and others did not. The findings indicate that future research should focus on enhancing subjective enjoyment of music.

This paper proposes a filter selection algorithm of virtual sensing for feedback active noise control system tracking noise variations. The proposed system maintains noise reduction performance by switching to an optimal noise control filter according to variations in noise characteristics. Noise variations are detected using bandpass filters with different frequency responses, and the optimal noise control filter is selected based on these detections. The auxiliary filter in virtual sensing is then re-estimated to track the variation in the noise control filter. Simulation results with actual impulse responses show that the proposed system can maintain a noise reduction of approximately 10 dB even when the noise varies.

In a previous paper, it was shown that the Kato model, with the material density and fiber diameter, can be used as a predictive model that enables the acoustic design (optimization of the fiber mixing rate) of fibrous materials. However, it does not have sufficient analytical precision for a material with high-bulk-density, so the model has limited applicability. Also, since the material density and fiber diameter are required as parameters, the Kato model cannot be applied to fibrous materials or foamed materials, the parameters of which are unknown. To solve these problems, in this paper, a technique of applying the Kato model to fibrous materials with high-bulk-density, fibrous materials with unknown material density and fiber diameter, and foamed materials is shown to extend its application.

The perception of speaker's facing directions is reflected radiation characteristics, which have an important role particularly in the immersive media. In the current study, we investigated the identification of speaker's facing directions through two experiments: one with (Exp. A) and one without (Exp. B) differences in loudness, targeting the horizontal plane at 0°, 45°, 90°, 135°, and 180°. The results of Exp. A suggested that participants mainly relied on loudness to identify speaker's facing directions, whereas Exp. B suggested that identification could be judged from some acoustic cues such as the spectral component of the sound instead of loudness.

Ball and tire impact sources are used as standard heavy-weight impact sources to induce heavy-weight impact sound. To predict the impact sound insulation performance accurately, the modeling of impact sources is important. In this paper, new single-degree-of-freedom (SDOF) models are proposed. Numerical calculations validate that using the proposed SDOF models can predict the impact force exposure levels accurately. Then, a numerical example is used to investigate changes in impact force exposure levels when impact sources acting on the dry-type double floor system.