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Wyświetlanie 1-2 z 2
Tytuł:
Study and Assessment of Low Frequency Noise in Occupational Settings
Autorzy:
Shehap, A. M.
Shawky, H. A.
El-Basheer, T. M.
Powiązania:
https://bibliotekanauki.pl/articles/177844.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
low frequency noise
A-weighting
C-weighting
audible
method of assessment
Opis:
Low frequency noise is one of the most harmful factors occurring in human working and living environment. Low frequency noise components from 20 to 250 Hz are often the cause of employee complaints. Noise from power stations is an actual problem for large cities, including Cairo. The noise from equipments of station could be a serious problem for station and for environmental area. The development of power stations in Cairo leads to appearing a wide range of gas turbines which are strong source of noise. Two measurement techniques using C-weighted along side the A-weighted scale are explored. C-weighting is far more sensitive to detect low frequency sound. Spectrum analysis in the low frequency range is done in order to identify a significant tonal component. Field studies were supported by a questionnaire to determine whether sociological or other factors might influence the results by using annoyance rating mean value. Subjects included in the study were 153 (mean = 36.86, SD = 8.49) male employees at the three electrical power stations. The (C-A) level difference is an appropriate metric for indicating a potential low frequency noise problem. A-weighting characteristics seem to be able to predict quite accurately annoyance experienced from LFN at workplaces. The aim of the present study is to find simple and reliable method for assessing low frequency noise in occupational environment to prevent its effects on work performance for the workers. The proposed method has to be compared with European methods.
Źródło:
Archives of Acoustics; 2016, 41, 1; 151-160
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Effective Speaker Clustering Method using UBM and Ultra-Short Training Utterances
Autorzy:
Hossa, R.
Makowski, R.
Powiązania:
https://bibliotekanauki.pl/articles/176593.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
automatic speech recognition
interindividual difference compensation
speaker clustering
universal background model
GMM weighting factor adaptation
Opis:
The same speech sounds (phones) produced by different speakers can sometimes exhibit significant differences. Therefore, it is essential to use algorithms compensating these differences in ASR systems. Speaker clustering is an attractive solution to the compensation problem, as it does not require long utterances or high computational effort at the recognition stage. The report proposes a clustering method based solely on adaptation of UBM model weights. This solution has turned out to be effective even when using a very short utterance. The obtained improvement of frame recognition quality measured by means of frame error rate is over 5%. It is noteworthy that this improvement concerns all vowels, even though the clustering discussed in this report was based only on the phoneme a. This indicates a strong correlation between the articulation of different vowels, which is probably related to the size of the vocal tract.
Źródło:
Archives of Acoustics; 2016, 41, 1; 107-118
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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