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Number of results: 8
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Abstract

Chinese is a tonal language, which differentiates it from non-tonal languages in the Western countries. A Chinese character consists of an initial, a final, and a tone. In the present study, the effects of noise and reverberation on the Chinese syllable, initial, final, and tone identification in rooms were investigated by using simulated binaural impulse responses through auralization method. The results show that the syllable identification score is the lowest, the tone identification score is the highest, and the initial identification scores are lower than those of the final identification under the same reverberation time and signal-to-noise ratio condition. The Chinese syllable, initial, and final identification scores increase with the increase of signal-to-noise ratio and decrease of the reverberation time. The noise and reverberation have insignificant effects on the Chinese tone identification scores under most room acoustical environments. The statistical relationship between the Chinese syllable articulation and phoneme articulation had been experimentally proved under different noise and reverberation conditions in simulated rooms.
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Authors and Affiliations

Jianxin Peng
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Abstract

The Chinese word identification and sentence intelligibility are evaluated by grades 3 and 5 students in the classrooms with different reverberation times (RTs) from three primary school under different signal-to-noise ratios (SNRs). The relationships between subjective word identification and sentence in- telligibility scores and speech transmission index (STI) are analyzed. The results show that both Chinese word identification and sentence intelligibility scores for grades 3 and 5 students in the classroom in- creased with the increase of SNR (and STI), increased with the increase of the age of students, and decreased with the increase of RT. To achieve a 99% sentence intelligibility score, the STIs required for grades 3, grade 5 students, and adults are 0.71, 0.61, and 0.51, respectively. The required objective acoustical index determined by a certain threshold of the word identification test might be underestimated for younger children (grade 3 students) in classroom but overestimated for adults. A method based on the sentence test is more useful for speech intelligibility evaluation in classrooms than that based on the word test for different age groups. Younger children need more favorable classroom acoustical environment with a higher STI than older children and adults to achieve the optimum speech communication in the classroom.
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Authors and Affiliations

Jianxin Peng
Peng Jiang
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Abstract

Acoustical analysis of snoring provides a new approach for the diagnosis of obstructive sleep apnea hypopnea syndrome (OSAHS). A classification method is presented based on respiratory disorder events to predict the apnea-hypopnea index (AHI) of OSAHS patients. The acoustical features of snoring were extracted from a full night’s recording of 6 OSAHS patients, and regular snoring sounds and snoring sounds related to respiratory disorder events were classified using a support vector machine (SVM) method. The mean recognition rate for simple snoring sounds and snoring sounds related to respiratory disorder events is more than 91.14% by using the grid search, a genetic algorithm and particle swarm optimization methods. The predicted AHI from the present study has a high correlation with the AHI from polysomnography and the correlation coefficient is 0.976. These results demonstrate that the proposed method can classify the snoring sounds of OSAHS patients and can be used to provide guidance for diagnosis of OSAHS.

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Authors and Affiliations

Can Wang
Jianxin Peng
Xiaowen Zhang
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Abstract

A questionnaire survey was conducted in the residential quarters of Guangzhou, for which 582 elderly people over 60 years old were randomly recruited. The hearing impairment of the participants was evaluated using the Hearing Handicap Inventory for the Elderly (HHIE), The participants’ subjective responses to the acoustical environment of their living place and the impact of the living acoustical environment (LAE) on the participants were investigated. The results show that the participants with a low HHIE score and no hearing impairment evaluated their LAE more favourably, and they considered that the effect of the LAE on their daily life was weak. However, those with a high HHIE score and severe hearing impairment evaluated their LAE poorly, and considered its effect on their daily lives to be significant. For the elderly, the worse the hearing is, the higher their demand for a better LAE. Traffic, construction, residential quarters, and noise from next door or upstairs neighbours were the main noise sources in the elderly’s living places, and traffic noise, construction noise, and noise from next door and upstairs were the most influential sources. 28.9% of the respondents had trouble hearing what their family said in their living place. The elderly without hearing impairment considered that continuous noise was the main reason that they could not hear what their family said in their living place, while those with hearing impairment believed that their own hearing problem was a contributing factor.

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Authors and Affiliations

Zeng Youjie
Peng Jianxin
Zhao Lei
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Abstract

In this paper, the relationship between Chinese speech intelligibility (CSI) scores of the elderly aged 60–69 and over 70 years old, and speech transmission index (STI) were investigated through the auralization method under different reverberation time and background noise levels (BNL, 40 dBA and 55 dBA). The results show that the CSI scores of the elderly are significantly worse than those of young adults. For the elderly over 70, the CSI scores become much lower than those of young adults. To be able to achieve the same CSI, the elderly, especially those over 70, need much higher STI and greater SNR than the young. The elderly aged 60–69 and over 70 need to improve their STI by 0.419 and 0.058 respectively under BNL 40 dBA, as well as 0.282 and 0.072 respectively under BNL 55 dBA, so as to obtain the same CSI scores as the young adults.
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Authors and Affiliations

Jianxin Peng
1 2
Jiazhong Zeng
3
Yuezhe Zhao
2

  1. School of Physics and Optoelectronics, South China University of Technology, Guangzhou, Guangdong, China, 510640
  2. State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, Guangdong, China, 510640
  3. School of Architecture, South China University of Technology, Guangzhou, Guangdong, China, 510640
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Abstract

Reverberation time (RT) is an important indicator of room acoustics, however, most studies focus on the mid-high frequency RT, and less on the low-frequency RT. In this paper, a hybrid approach based on geometric and wave methods was proposed to build a more accurate and wide frequency-band room acoustic impulse response. This hybrid method utilized the finite-difference time-domain (FDTD) method modeling at low frequencies and the Odeon simulation at mid-high frequencies, which was investigated in a university classroom. The influence of the low-frequency RT on speech intelligibility was explored. For the low-frequency part, different impedance boundary conditions were employed and the effectiveness of the hybrid method has also been verified. From the results of objective acoustical parameters and subjective listening experiments, the smaller the low-frequency RT was, the higher the Chinese speech intelligibility score was. The syllables, consonants, vowels, and the syllable order also had significant effects on the intelligibility score.
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Authors and Affiliations

Wuqiong Huang
1 2
Jianxin Peng
1
Tinghui Xie
3

  1. School of Physics and Optoelectronics, South China University of Technology, Guangzhou, China
  2. State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, China
  3. School of Architecture and Art, Shijiazhuang Tiedao University, Shijiazhuang, China
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Abstract

Snoring is a typical and intuitive symptom of the obstructive sleep apnea hypopnea syndrome (OSAHS), which is a kind of sleep-related respiratory disorder having adverse effects on people’s lives. Detecting snoring sounds from the whole night recorded sounds is the first but the most important step for the snoring analysis of OSAHS. An automatic snoring detection system based on the wavelet packet transform (WPT) with an eXtreme Gradient Boosting (XGBoost) classifier is proposed in the paper, which recognizes snoring sounds from the enhanced episodes by the generalization subspace noise reduction algorithm. The feature selection technology based on correlation analysis is applied to select the most discriminative WPT features. The selected features yield a high sensitivity of 97.27% and a precision of 96.48% on the test set. The recognition performance demonstrates that WPT is effective in the analysis of snoring and non-snoring sounds, and the difference is exhibited much more comprehensively by sub-bands with smaller frequency ranges. The distribution of snoring sound is mainly on the middle and low frequency parts, there is also evident difference between snoring and non-snoring sounds on the high frequency part.
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Authors and Affiliations

Li Ding
1
Jianxin Peng
1
Xiaowen Zhang
2
Lijuan Song
2

  1. School of Physics and Optoelectronics, South China University of Technology, Guangzhou, China
  2. State Key Laboratory of Respiratory Disease, Department of Otolaryngology-Head and Neck Surgery Laboratory of ENT-HNS Disease, First Affiliated Hospital, Guangzhou Medical University, Guangzhou, China

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