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Number of results: 5
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Driver Filter Design for Software-Implemented Loudspeaker Crossovers

Shu-Nung Yao
Archives of Acoustics | 2014 | vol. 39 | No 4 | 591-597 | DOI: 10.2478/aoa-2014-0063
Keywords crossover loudspeaker pole-zero placement Pascal matrix river filter
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Abstract

A hybrid method is presented for the integration of low-, mid-, and high-frequency driver filters in loud-speaker crossovers. The Pascal matrix is exploited to calculate denominators; the locations of minimum values in frequency magnitude responses are associated with the forms of numerators; the maximum values are used to compute gain factors. The forms of the resulting filters are based on the physical meanings of low-pass, band-pass, and high-pass filters, an intuitive idea which is easy to be understood. Moreover, each coefficient is believed to be simply calculated, an advantage which keeps the software-implemented crossover running smoothly even if crossover frequencies are being changed in real time. This characteristic allows users to efficiently adjust the bandwidths of the driver filters by subjective listening tests if objective measurements of loudspeaker parameters are unavailable. Instead of designing separate structures for a low-, mid-, and high-frequency driver filter, by using the proposed techniques we can implement one structure which merges three types of digital filters. Not only does the integration architecture operate with low computational cost, but its size is also compact. Design examples are included to illustrate the effectiveness of the presented methodology
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Authors and Affiliations

Shu-Nung Yao

Influence of Loudspeaker Configurations and Orientations on Sound Localization

Shu-Nung Yao
Archives of Acoustics | 2022 | vol. 47 | No 1 | 57-70 | DOI: 10.24425/aoa.2022.140732
Keywords audio quality ambisonics immersive sound loudspeaker array spatial effect virtual reality
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Abstract

As the virtual reality (VR) market is growing at a fast pace, numerous users and producers are emerging with the hope to navigate VR towards mainstream adoption. Although most solutions focus on providing highresolution and high-quality videos, the acoustics in VR is as important as visual cues for maintaining consistency with the natural world. We therefore investigate one of the most important audio solutions for VR applications: ambisonics. Several VR producers such as Google, HTC, and Facebook support the ambisonic audio format. Binaural ambisonics builds a virtual loudspeaker array over a VR headset, providing immersive sound. The configuration of the virtual loudspeaker influences the listening perception, as has been widely discussed in the literature. However, few studies have investigated the influence of the orientation of the virtual loudspeaker array. That is, the same loudspeaker arrays with different orientations can produce different spatial effects. This paper introduces a VR audio technique with optimal design and proposes a dual-mode audio solution. Both an objective measurement and a subjective listening test show that the proposed solution effectively enhances spatial audio quality.
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Authors and Affiliations

Shu-Nung Yao
1
  1. Department of Electrical Engineering, National Taipei University, No. 151, University Rd., Sanxia Dist., New Taipei City 237303, Taiwan

HRTF Adjustments with Audio Quality Assessments

Shu-Nung Yao Li Jen Chen
Archives of Acoustics | 2013 | vol. 38 | No 1 | 55-62 | DOI: 10.2478/aoa-2013-0007
Keywords HRTF PEAQ cone of confusion headphones surround
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Abstract

There are an increasing number of binaural systems embedded with head-related transfer functions (HRTFs), so listeners can experience virtual environments via conventional stereo loudspeakers or head- phones. As HRTFs vary from person to person, it is difficult to select appropriated HRTFs from already existing databases for users. Once the HRTFs in a binaural audio device hardly match the real ones of the users, poor localization happens especially on the cone of confusion. The most accurate way to obtain personalized HRTFs might be doing practical measurements. It is, however, expensive and time consuming. Modifying non-individualized HRTFs may be an effort-saving way, though the modifications are always accompanied by undesired audio distortion. This paper proposes a flexible HRTF adjustment system for users to define their own HRTFs. Also, the system can keep sounds from suffering intolerable distortion based on an objective measurement tool for evaluating the quality of processed audio.
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Authors and Affiliations

Shu-Nung Yao
Li Jen Chen

Head-Related Transfer Function Selection Using Neural Networks

Shu-Nung Yao Tim Collins Chaoyun Liang
Archives of Acoustics | 2017 | vol. 42 | No 3 | DOI: 10.1515/aoa-2017-0038
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Authors and Affiliations

Shu-Nung Yao
Tim Collins
Chaoyun Liang

Artificial Intelligence on the Identification of Beiguan Music

Yu-Hsin Chang Shu-Nung Yao
Archives of Acoustics | 2021 | vol. 46 | No 3 | 471-478 | DOI: 10.24425/aoa.2021.138139
Keywords artificial neural network Beiguan music music information retrieval social tagging
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Abstract

This research determines an identification system for the types of Beiguan music – a historical, nonclassical music genre – by combining artificial neural network (ANN), social tagging, and music information retrieval (MIR). Based on the strategy of social tagging, the procedure of this research includes: evaluating the qualifying features of 48 Beiguan music recordings, quantifying 11 music indexes representing tempo and instrumental features, feeding these sets of quantized data into a three-layered ANN, and executing three rounds of testing, with each round containing 30 times of identification. The result of ANN testing reaches a satisfying correctness (97% overall) on classifying three types of Beiguan music. The purpose of this research is to provide a general attesting method, which can identify diversities within the selected non-classical music genre, Beiguan. The research also quantifies significant musical indexes, which can be effectively identified. The advantages of this method include improving data processing efficiency, fast MIR, and evoking possible musical connections from the high-relation result of statistical analyses.
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Bibliography

1. Briot J.-P., Hadjeres G., Pachet F.-D. (2019), Deep Learning Techniques for Music Generation, Computational Synthesis and Creative Systems, Springer, arXiv: 1709.01620.
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6. Rosner A., Schuller B., Kostek B. (2014), Classification of music genres based on music separation into harmonic and drum components, Archives of Acoustics, 39(4): 629–638, doi: 10.2478/aoa-2014-0068.
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8. Wiering F., de Nooijer J., Volk A., Tabachneck- Schijf H.J.M. (2009), Cognition-based segmentation for music information retrieval systems, Journal of New Music Research, 38(2): 139–154, doi: 10.1080/09298210903171145.
9. Yao S.-N., Collins T., Liang C. (2017), Head-related transfer function selection using neural networks, Archives of Acoustics, 42(3): 365–373, doi: 10.1515/aoa-2017-0038.
10. Yeh N. (1988), Nanguan music repertoire: categories, notation, and performance practice, Asian Music, 19(2): 31–70, doi: 10.2307/833866.
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Authors and Affiliations

Yu-Hsin Chang
1
Shu-Nung Yao
2
  1. Department of Music, Tainan National University of the Arts, No. 66, Daqi, Guantian Dist., Tainan City 72045, Taiwan
  2. Department of Electrical Engineering, National Taipei University, No. 151, University Rd., Sanxia District, New Taipei City 237303, Taiwan

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