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.
In the external target experiment for heavy ion collisions in the HIRFL-CSR, Multi-Wire Drift Chambers are used to measure the drift time of charged particles to obtain the track information. This 128-channel high precision time measurement module is designed to perform the time digitization. The data transfer is based on a PXI interface to guarantee a high data rate. Test results show that a 100 ps resolution with a data transfer rate up to 40 MBps has been achieved; this module has also been proven to function well with the detector through a commissioning test.
A novel VC (voice conversion) method based on hybrid SVR (support vector regression) and GMM (Gaussian mixture model) is presented in the paper, the mapping abilities of SVR and GMM are exploited to map the spectral features of the source speaker to those of target ones. A new strategy of F0 transformation is also presented, the F0s are modeled with spectral features in a joint GMM and predicted from the converted spectral features using the SVR method. Subjective and objective tests are carried out to evaluate the VC performance; experimental results show that the converted speech using the proposed method can obtain a better quality than that using the state-of-the-art GMM method. Meanwhile, a VC method based on non-parallel data is also proposed, the speaker-specific information is investigated using the SVR method and preliminary subjective experiments demonstrate that the proposed method is feasible when a parallel corpus is not available.
Passive source localization in shallow water has always been an important and challenging problem. Implementing scientific research, surveying, and monitoring using a short, less than ten meter long, horizontal linear array has received considerable attention in the recent years. The short array can be conveniently placed on autonomous underwater vehicles and deployed for adaptive spatial sampling. However, it is usually difficult to obtain a sufficient spatial gain for localizing long-range sources due to its limited physical size. To address this problem, a localization approach is proposed which is based on matched-field processing of the likelihood of the passive source localization in shallow water, as well as inter-position processing for the improved localization performance and the enhanced stability of the estimation process. The ability of the proposed approach is examined through the two-dimensional synthetic test cases which involves ocean environmental mismatch and position errors of the short array. The presented results illustrate the localization performance for various source locations at different signal- to-noise ratios and demonstrate the build up over time of the positional parameters of the estimated source as the short array moves at a low speed along a straight line at a certain depth.
Speaker‘s emotional states are recognized from speech signal with Additive white Gaussian noise (AWGN). The influence of white noise on a typical emotion recogniztion system is studied. The emotion classifier is implemented with Gaussian mixture model (GMM). A Chinese speech emotion database is used for training and testing, which includes nine emotion classes (e.g. happiness, sadness, anger, surprise, fear, anxiety, hesitation, confidence and neutral state). Two speech enhancement algorithms are introduced for improved emotion classification. In the experiments, the Gaussian mixture model is trained on the clean speech data, while tested under AWGN with various signal to noise ratios (SNRs). The emotion class model and the dimension space model are both adopted for the evaluation of the emotion recognition system. Regarding the emotion class model, the nine emotion classes are classified. Considering the dimension space model, the arousal dimension and the valence dimension are classified into positive regions or negative regions. The experimental results show that the speech enhancement algorithms constantly improve the performance of our emotion recognition system under various SNRs, and the positive emotions are more likely to be miss-classified as negative emotions under white noise environment.
The Silurian fishes from north-western Hunan, China are characterised by the earliest known galeaspids Dayongaspis Pan and Zeng, 1985 and Konoceraspis Pan, 1992, and the earliest known antiarch Shimenolepis Wang J.-Q., 1991, as well as rich sinacanth fin spines. Shimenolepis from Lixian County in north-western Hunan, which was dated as the Telychian (late Llandovery), has long been regarded as the oldest representative of the placoderms in the world. As such, in addition to eastern Yunnan and the Lower Yangtze Region, north-western Hunan represents another important area in South China that yields important fossil material for the research of early vertebrates and related stratigraphy. Here we summarise the Silurian fishes known in north-western Hunan so far, and classify them into three vertebrate assemblages (i.e., the Wentang, Maoshan, and Yangtze assemblages). Based on the updated Silurian vertebrate and stratigraphic databases, the Silurian fish-bearing strata in north-western Hunan can be subdivided into the Rongxi, Huixingshao, and Xiaoxi formations in ascending chronological order, which can be correlated with the Lower Red Beds, the Upper Red Beds, and the Ludlow Red Beds in South China, respectively. A new look at the Silurian strata in Lixian suggests that the age of Shimenolepis is late Ludlow rather than late Llandovery as previously suggested. The research on Silurian fishes and biostratigraphy in north-western Hunan not only provides morphological data of early vertebrates, but also offers new palaeoichthyological evidence for the subdivision, correlation, and age assignment of the Silurian marine red beds in South China. The establishment of a related high-precision Silurian stratigraphic framework in north-western Hunan will help to elucidate the temporal and spatial distribution of Silurian fossil fishes, deepen the understanding of the evolution of early vertebrates, and unravel the coevolution between Silurian vertebrates and the palaeoenvironment.