psychoacoustic model
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2021 ◽  
Vol 13 (11) ◽  
pp. 5779
Author(s):  
Ferran Orga ◽  
Andrew Mitchell ◽  
Marc Freixes ◽  
Francesco Aletta ◽  
Rosa Ma Alsina-Pagès ◽  
...  

The recent development and deployment of Wireless Acoustic Sensor Networks (WASN) present new ways to address urban acoustic challenges in a smart city context. A focus on improving quality of life forms the core of smart-city design paradigms and cannot be limited to simply measuring objective environmental factors, but should also consider the perceptual, psychological and health impacts on citizens. This study therefore makes use of short (1–2.7 s) recordings sourced from a WASN in Milan which were grouped into various environmental sound source types and given an annoyance rating via an online survey with N=100 participants. A multilevel psychoacoustic model was found to achieve an overall R2=0.64 which incorporates Sharpness as a fixed effect regardless of the sound source type and Roughness, Impulsiveness and Tonality as random effects whose coefficients vary depending on the sound source. These results present a promising step toward implementing an on-sensor annoyance model which incorporates psychoacoustic features and sound source type, and is ultimately not dependent on sound level.


2021 ◽  
Vol 149 (1) ◽  
pp. 457-465
Author(s):  
Jody Kreiman ◽  
Yoonjeong Lee ◽  
Marc Garellek ◽  
Robin Samlan ◽  
Bruce R. Gerratt

2020 ◽  
Vol 14 (4) ◽  
pp. 125-136
Author(s):  
A. G. Boyarov ◽  
I. S. Siparov

Special aspects of MP3-recordings technical investigation are addressed. The following features of formation and research of MP3 phonograms are explained: traces of MP3 coding in time and spectral domain, special aspects of MP3-files structure analysis, detection methods of re-coding of MP3-recordings, methods of group identification of MP3-recorders and MP3-codecs.MP3 coding leaves certain traces of its usage. Due to the psychoacoustic model inaudible spectral components are deleted from the signal spectrum. Traces of psychoacoustic codecs usage are also clearly seen via dynamic spectrogram as rectangular areas of zero spectral amplitude. The methods discussed in this paper enable the investigating expert to detect the exact position of the MP3 frame in the signal by its properties even without any information from the file header. This method reveals the coding itself, multiple coding and also audio editing by the investigation of the periodicity of the extracted frames’ positions.MP3 file format specifies the structure of the frame header providing a perfect instrument to detect any periodicity of any peculiarities of MP3 frames. The tool based on this approach reveals MP3 frames disorder caused by editing in the “digital” domain – manual deletion of audio information using HEX editor.


2019 ◽  
Vol 24 (4) ◽  
pp. 728-735
Author(s):  
Mourad Talbi ◽  
Med Salim Bouhlel

In this paper, a new speech compression technique is proposed. This technique applies a Psychoacoustic Model and a general approach for Filter Bank Design using optimization. It is evaluated and compared with a compression technique using a MDCT (Modified Discrete Cosine Transform) Filter Bank of 32 Filters and a Psychoacoustic Model. This evaluation and comparison is performed by calculating bits before and after compression, PSNR (Peak Signal to Noise Ratio), NRMSE (Normalized Root Mean Square Error), SNR (Signal to Noise Ratio) and PESQ (Perceptual evaluation of speech quality) computations. The two techniques are tested and applied to a number of speech signals that are sampled at 8 kHz. The results obtained from this evaluation show that the proposed technique outperforms the second compression technique (based on a Psychoacoustic Model and MDCT filter Bank) in terms of Bits after compression and compression ratio. In fact, the proposed technique yields higher values for the compression ratio than the second compression technique. Moreover, the proposed compression technique presents reconstructed speech signals with acceptable perceptual qualities. This is justified by the values of SNR, PSNR and NRMSE and PESQ.


2019 ◽  
Vol 14 (8) ◽  
pp. 2217-2231 ◽  
Author(s):  
Xiaowei Yi ◽  
Kun Yang ◽  
Xianfeng Zhao ◽  
Yuntao Wang ◽  
Haibo Yu

2018 ◽  
Vol 140 ◽  
pp. 178-182 ◽  
Author(s):  
Marek Moravec ◽  
Gabriela Ižaríková ◽  
Pavol Liptai ◽  
Miroslav Badida ◽  
Anna Badidová

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