Intelligibility Test Research Articles

Intellectualized testing & evaluation application based on unmanned test platform

Taking three pure electric vehicles as the research object, the energy consumption and acceleration performance of the electric vehicle are tested and evaluated through the use of the intelligent unmanned test platform of the whole vehicle, which ensures that the accurate and high-speed test of the road test can be realized on the basis of no driver in the vehicle. For the electric vehicle energy consumption test, the intelligent unmanned test platform is used for road test, which not only effectively avoids the driver driving the test vehicle for a long time, but also ensures the accuracy and reliability of the test data. According to the test results, the acceleration response and energy consumption test results of three pure electric vehicles are analyzed and evaluated.

Power Exponent Based Weighting Criterion for DNN-Based Mask Approximation in Speech Enhancement

In this letter, a novel weighted mean square error (WMSE) is proposed to improve the DNN-based mask approximation method for speech enhancement, in which the weighting is closely related to the power exponent about noisy spectrum amplitude (NSA) base. The power exponents 0 and 2 separately reflect ideal amplitude masking (IAM) without any clippings and the indirect mapping (IM) on short-time spectral amplitude (STSA), and it is highly related to the enhanced spectrum and the performance of the enhanced signal based on the tests. Also, the experimental results show that the outstanding weighting is the noisy spectrum base with the power exponent 1 for the phase-unaware masking and results in better harmonic structure restoration. The objective function with the WMSE on the NSA (WMSE-NSA) can averagely improve 0.1 on the test of perceptual evaluation of speech quality (PESQ) and 1.7% on the test of short-time objective intelligibility (STOI) compared with the MSE-based mask approximation methods.

The Establishment and Exploration of Diversified High Level Engineering Practice Education Platform

Practical teaching is not only an important link in the process of cultivating applied talents, but also an important means to improve students' engineering application ability and innovation ability. In order to cultivate high-level application-oriented talents, aiming at the current lack of digital and intelligent knowledge among college students and the lack of "personalized" specialty, this research group adheres to engineering practice education as the main line, aims at cultivating application-oriented talents in engineering, and features in improving students' innovation ability. With the construction of new curriculum system, new innovation and entrepreneurship system and new practical teaching system as the core, it has built a diversified high-level engineering education practice platform integrating digital analysis and simulation, intelligent manufacturing and testing, and virtual simulation of production process. Explore its own distinctive characteristics of high-level application-oriented talent training new mode and new ways, cultivate students' innovative thinking and the ability to solve practical problems, in mechanical design ability has been rapidly improved, become an expert in design. At the same time, the level of intelligent manufacturing and intelligent detection has been improved, and personalized high-end talents with both professional knowledge and digital and intelligent knowledge have been refined to meet the social demand for such technical compound talents.

Agent based simulation for the design of a mobility service in the Paris-Saclay area

Autonomous vehicles promise an important opportunity for a complete paradigm shift for the design of transportation systems. These systems will become more flexible and efficient by adapting to the travelers’ demand. On the other hand, multi agent systems offer an intuitive and powerful way to design complex distributed systems and agent based simulation has proved to be well suited for studying the performance of mobility services and their impact on the users and the traffic in general.In this study, we use an Agent-Based modeling approach to design a mobility system based on a fleet of autonomous vehicles (robo-taxis and shuttles) and connected road side units, each of these elements represented by intelligent collaborative agents. In our model, the control is distributed among the agents and the global behaviour of the system emerges from local decisions. We then used a microsimulation tool to test the model on the real road network of the Paris-Saclay area. Since this area is planned to become a center for technology, innovation and education and is currently under constant development, it offers an opportunity for the design and the implementation of new models of transportation services.We designed our mobility system in an incremental manner by introducing more components and more intelligent behaviour and testing its performance at each step.Our results suggest that for our area of study, a mobility service that relies on autonomous vehicles aided by connected road side units that allow to retrieve information about the traffic would perform better than a regular service.

Intelligent network management system for solving the problem of offline monitoring 5G technologies

Maintenance and management of fourth-generation (4G) current networks are still done manually and semi-automatically, which is expensive and time-consuming. This poses a major challenge for network management of disparate, software-defined, and virtualized fifth-generation (5G) systems. Fifth-generation (5G) cellular networks include a wide variety of technologies to address very different uses. Assessing these technologies and exploring future alternatives is complicated by relying solely on network administrators. 5G network intelligence is an important alternative to network administrators. With the advent of network intelligence for the 5G system opens the possibility of intelligent control. Without the intervention of administrators, the new approach can autonomously solve network problems, cyberattacks and inefficient use of resources, which in turn can reduce operating costs, improve user experience and reduce the time to market of new services. This work presents a test bench of a 5G mobile network with a virtualized and organized structure that focuses on integration into artificial intelligence programs. The presented test bench uses open-source technologies for deployment and orchestration of virtual network functions for flexible creation of various scenarios of mobile networks with clear topologies of frontal and feedback. The article explains how to deploy the structure of the test bench and reproduce the presented results with the provided algorithms and presents the recommended architecture, functionality, closed control, algorithms that include network intelligence. An intelligent 5G test bench has been installed, and experimental results confirm the feasibility and effectiveness.

A framework for intelligent IoT firmware compliance testing

The recent mass production and usage of the Internet of Things (IoT) have posed serious concerns due to the unavoidable security complications. The firmware of IoT systems is a critical component of IoT security. Although multiple organizations have released security guidelines, few IoT vendors are following these guidelines properly, either due to a lack of accountability or the availability of appropriate resources. Some tools for this purpose can use static, dynamic, or fuzzing techniques to test the security of IoT firmware, which may result in false positives or failure to discover vulnerabilities. Furthermore, the vast majority of resources are devoted to a single subject, such as networking protocols, web interfaces, or Internet of Things computer applications. This paper aims to present a novel method for conducting compliance testing and vulnerability evaluation on IoT system firmware, communication interfaces, and networking services using static and dynamic analysis. The proposed system detects a broad range of security bugs across a wide range of platforms and hardware architectures. To test and validate our prototype, we ran tests on 4300 firmware images and discovered 13,000+ compliance issues. This work, we believe, will be the first step toward developing a reliable automated compliance testing framework for the IoT manufacturing industry and other stakeholders.

Combination and Comparison of Sound Coding Strategies Using Cochlear Implant Simulation With Mandarin Speech.

Three cochlear implant (CI) sound coding strategies were combined in the same signal processing path and compared for speech intelligibility with vocoded Mandarin sentences. The three CI coding strategies, biologically-inspired hearing aid algorithm (BioAid), envelope enhancement (EE), and fundamental frequency modulation (F0mod), were combined with the advanced combination encoder (ACE) strategy. Hence, four singular coding strategies and four combinational coding strategies were derived. Mandarin sentences with speech-shape noise were processed using these coding strategies. Speech understanding of vocoded Mandarin sentences was evaluated using short-time objective intelligibility (STOI) and subjective sentence recognition tests with normal-hearing listeners. For signal-to-noise ratios at 5 dB or above, the EE strategy had slightly higher average scores in both STOI and listening tests compared to ACE. The addition of EE to BioAid slightly increased the mean scores for BioAid+EE, which was the combination strategy with the highest scores in both objective and subjective speech intelligibility. The benefits of BioAid, F0mod, and the four combinational coding strategies were not observed in CI simulation. The findings of this study may be useful for the future design of coding strategies and related studies with Mandarin.

Effects of Subthalamic Nucleus Deep Brain Stimulation Surgery on Voice and Formant Frequencies of Vowels in Turkish.

To investigate the effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN) on acoustic characteristics of voice production in Turkish patients with Parkinson's disease (PD). This study recruited 20 patients diagnosed with PD. Voice samples were recorded under the "stimulation on" and "stimulation off" conditions of STN-DBS. Acoustic recordings of the patients were made during the production of vowels /a/, /o/, and /i/ and repetition of the syllables /pa/-/ta/-/ka/. Acoustic analyses were performed using Praat. A significant difference in the parameters was observed among groups for vowels. A positive significant difference was observed between preoperative med-on and postoperative med-on/stim-on groups for /a/ and the postoperative med-on/ stim-on and postoperative med-on/stim-off groups for /o/ and /i/ for frequency perturbation (jitter) and noise-to-harmonics ratio. No significant difference was noted between the preoperative med-on and postoperative med-on/stim-off groups for any vowels. STN-DBS surgery has an acute positive effect on voice. Studies on formant frequency analysis in STN-DBS may be expanded with both articulation and intelligibility tests to enable us to combine patient abilities in various perspectives and to obtain precise results.

Effects Of Removable Anterior Expansion Screw on Speech Intelligibility In a Group of Egyptian Children

Abstract Aim : This study was conducted to evaluate the speech disorders that could be reported after insertion of removable anterior expansion screw appliances used for correction of anterior dental crossbite. Materials and Methods: Fifty children with mean age (9.36±0.99 years) and diagnosed to have anterior dental crossbite. The anterior crossbite was planned to be corrected with removable anterior screw and posterior bite plane. Speech evaluation (including: articulation test and speech intelligibility test) was performed ; before appliance insertion , immediately after appliance insertion , one weeh after appliance insertion and finally after one month from appliance insertion . Results : Before appliance insertion, all sounds were intact for the majority of the cases 42(84%). Immediately after insertion, all the cases had difficulty in producing /s/, /s. /, /z/ sounds (100%). After one week of insertion, majority of the cases 30(60%) still had difficulty in producing the same sounds. While, After one month of insertion, most of the cases 40(80%) had no problem in producing different sounds . Conclusion : The speech performance while using removable anterior expansion screw for was worst immediately after placement of the appliance and 1 week respectively and improved after one month of appliance insertion.

The information security transmission method for intelligent examination based on ZigBee communication

Aiming at the problems of low network utilisation, poor security and high cost in the traditional intelligent test information security transmission method, a ZigBee communication-based information security intelligent detection and transmission method is proposed. Network key and connection key are realised by using asymmetric key system. Public key encryption and private key decryption are used to verify the trust centre. The sending node uses the trust centre to get the public key of the target node so as to achieve the goal of the intelligent test information security transmission. The simulation results show that the network utilisation rate is above 96%, compared with the traditional method, the index level has been significantly improved. The efficiency of the proposed method is up to 99%. In terms of cost, the proposed method has a lower cost. When the running time reaches 920 min, the cost is RMB 17,000 yuan.

Analysis of intelligent test paper generation method for online examination based on UML and particle swarm optimisation

Analysis of intelligent test paper generation method for online examination based on UML and particle swarm optimisation

Abnormal state recognition method for online intelligent examination based on improved genetic algorithm

In order to overcome the defects of the traditional test monitoring scheme, this paper proposes a new method of online intelligent test abnormal state recognition based on improved genetic algorithm. This method sets the test status parameters and defines the criteria of abnormal status, collects the online test information and builds the information database. Image preprocessing is realised from two aspects of image segmentation and greyscale processing. The improved genetic algorithm is used to analyse and collect data intelligently and search image feature points to obtain abnormal feature extraction results. Match the extracted feature results with the established database information to realise the abnormal state recognition results, and start the corresponding abnormal alarm program. The experimental results show that the accuracy of the proposed method is 18.57% higher than that of the traditional method, indicating that the method has a better application prospect.

Analysis of intelligent test paper generation method for online examination based on UML and particle swarm optimisation

In order to overcome the problems of unclear objective function and inaccurate optimal solution in traditional test paper generation methods, an online intelligent test paper generation method based on UML and particle swarm optimisation is proposed. A mathematical model of test paper generation based on UML modelling tool is established, and the objective function of test paper generation is obtained. The improved particle swarm optimisation algorithm is used to solve the objective function of test paper generation. The optimal solution of the objective function is introduced into the question bank. The test questions in the test bank are combined and imported into the online examination system to realise the intelligent test paper formation of online examination. The experimental results show that this method has strong adaptability and can achieve better performance than the traditional intelligent test paper generation method.

Fuzzy control based on genetic algorithm in intelligent psychology teaching system

The advancement of science has made computer technology and the education industry more and more closely related, and the development of intelligent teaching systems has also opened a new path for classroom teaching. This paper studies the application of fuzzy control based on genetic algorithms in the intelligent psychology teaching system. Facing the complicated variables in the teaching process, the improved genetic algorithm can better realize dynamic teaching decisions through fuzzy control. This article aims to improve the quality of psychology classroom teaching, and develops an intelligent psychology teaching system based on the fuzzy control theory of genetic algorithm. Combined with the current development of fuzzy control theory, the problems existing in the intelligent teaching system are studied and analyzed, and they have been optimized and improved. This paper proposes a control algorithm based on a teaching management system. The algorithm can implement fuzzy control on student models, knowledge organization structure, intelligent test papers and teaching decision-making. While restoring the real teaching process, it can better realize teaching students in accordance with their aptitude and improve teaching. The intelligence of the system. According to the system test data, the proportions of the difficulty of the system’s automatic test paper are 30.1%, 51.6%, 18.3%, which are in line with the designer’s set expectation of 3 : 5:2, which shows the improved genetic algorithm. It can realize the intelligent volume group function very well.

Dutch speech intelligibility in bilingual Turkish-Dutch children in Flanders

AbstractThis study examines the Dutch intelligibility of a group of monolingual Dutch and bilingual Turkish-Dutch preschool children in Flanders, as rated by native Dutch listeners and measured by a Dutch intelligibility test. The intelligibility of the bilingual children is compared to that of the monolingual Dutch children, in order to examine whether age and/or task effects are similar or different in the two groups. The results revealed that intelligibility was affected by age, but showed no significant interaction between age and group. However, we found a significant interaction between age and task: children’s intelligibility increased with age for a word production as well as a sentence production task, but much more so for the latter than for the former. We discuss the results in relation to the children’s developing phonological systems, the age of exposure to Dutch and the nature of the test.

Computer Intelligent Test Paper System Based on Genetic Algorithm

The rapid development of the Internet has brought tremendous changes to people’s lives. Through the network function, the online examination is gradually accepted by various educational and teaching institutions. Currently, online exams have become the main method of teaching evaluation. In order to solve the problem of intelligent test paper more effectively, this paper proposes a mufti-threaded intelligent test paper strategy based on genetic algorithm, and designs the computer system structure in the standard test question bank. Convergence simulation and experimental results show that the algorithm is better than simple particle swarm optimization algorithm, simple genetic algorithm and its improved algorithm. Established a mathematical model and objective function for test paper composition, and proposed an intelligent test paper composition strategy based on genetic algorithm. The investigator used overall coding, crossover and mutation operations to improve the global optimization capability and convergence speed. It overcomes the phenomenon of premature and improves the accuracy and speed of convergence. It has the advantages of strong optimization ability and good stability.

Analysis on the Multiple Intelligences of Students from Faculty of Physical Education and Sports

The present research is based on the theory developed in 1983 by the American psychologist Howard Gardner, according to which people possess eight distinct types of intelligence: verbal/ linguistic, mathematical/ logical, visual/ spatial, bodily/ kinesthetic, rhythmic/ musical, interpersonal, intrapersonal, naturalist. The way these multiple intelligences are combined differentiates us as humans, for example, in school, students react differently. Some students are more interested in learning, some are not. This may be due to different types of intelligence. Our research aims to highlight the dominant types of intelligence for second year students, depending on which teachers can adapt their teaching methods. The research was carried out over a period of 3 weeks. The participants in the research are 111 romanian students from National University of Physical Education and Sports, out of which 42 are female and 69 are male. The research methods used are: scientific documentation, questionnaire-based survey (multiple intelligences test was applied), statistical-mathematical method, graphical method. The results of the research provide us important data to see to what extent kinesthetic body intelligence is dominant in students practicing sports and what are the other types of intelligence present in athletes. Finding out the dominant types of student’s intelligence can provide us important information according to which we can adapt our teaching methods. Thus, we can conduct our didactic activity in an attractive manner, in which the potential of students is not wasted and feel motivated to learn and evolve in a traditional classroom.

Evaluation of speech enhancement algorithms applied to electrolaryngeal speech degraded by noise

Electrolaryngeal speech, for persons who have lost their larynx, suffers from the drawback of susceptibility to acoustic noise, which includes inherent electrolarynx motor noise as well as environmental noise. Interactions with electrolarynx users motivated the authors to investigate a crucial drawback of electrolaryngeal speech: degradation of electrolaryngeal speech under noisy environments. The effect of contemporary methods of speech enhancement, viz. noise power spectral density estimation based d-dimensional amplitude trimmed estimation (DATE), and non-negative matrix factorization (NMF) based algorithms, were studied and evaluated for electrolaryngeal speech degraded by noise. Electrolaryngeal speech was corrupted using three types of noisy scenarios at low signal to noise ratios (0, −5 and −10 dB SNR). Objective testing based on the perceptual evaluation of speech quality (PESQ) standard, as well as subjective testing by 14 participants based on the ITU-T P.835 standard were performed. Word-centric intelligibility testing was also performed. The results indicated an improvement in the speech quality. The subjective testing results were further analyzed using one-way analysis of variance (ANOVA) and multiple paired comparison using Tukey’s honest significant difference (HSD) criterion. The overall speech quality of NMF algorithms was found to be significantly higher than that of DATE-based algorithms for the test conditions. The results show that speech enhancement algorithms can aid in improving the electrolaryngeal user experience by reducing the effect of acoustic noise.

Construction of intelligent testing system for electronic components

In order to solve the problems such as unreasonable plan, opaque process, insufficient flexibility and excessive manual participation in the process of screening, identification and quality consistency inspection of electronic components in China, a software and hardware construction scheme of intelligent detection system for electronic components is proposed, which integrates the cutting-edge technologies such as machine vision, deep learning, IOT(internet of things), data mining. Relying on the National Semiconductor Device Quality Supervision and Inspection Center, part of the construction work has been completed, and the information, automation and intelligence of the testing business have been realized.

Speech intelligibility test methodology applied to powered air-purifying respirators used in healthcare

Powered air-purifying respirators (PAPRs) are worn to protect workers from hazardous respiratory exposures in a wide range of workplaces, including healthcare. However, PAPRs may diminish the ability of wearers to correctly hear words spoken by others, potentially interfering with safe performance of healthcare duties. Accordingly, the impact of PAPRs during healthcare use on speech intelligibility (SI) and consequently on user safety, usability, and patient care is not well studied. The objectives of this study were to (1) determine a listener’s ability to comprehend single-syllable words spoken by a PAPR wearer; (2) determine a PAPR wearer’s ability to intelligibly hear and identify single-syllable words spoken by a PAPR wearer; (3) to assess the variability between speakers, listeners, and PAPR models; (4) to investigate the effects of PAPR design features on SI; and (5) inform a SI requirement for certifying future PAPRs for use in healthcare. This study utilized a Modified Rhyme Test to assess SI for PAPRs. The current National Institute for Occupational Safety and Health (NIOSH) methods for assessing SI are limited to the recently introduced PAPR100 respirator class and the class of respirators claiming chemical, biological, radiological, and nuclear (CBRN) protections. Four NIOSH-approved PAPRs were evaluated using four human subjects. Four experimental conditions were examined:(1) Speaker and Listener with no PAPR; (2) Speaker and Listener both wearing PAPRs; (3) Speaker with a PAPR, Listener without a PAPR; and (4) Speaker without a PAPR, Listener with a PAPR resulted in a total of 144 experiments. Statistical analysis showed that the SI performance ratings were not significantly different among the PAPR models, but experimental conditions had significant impact on SI. The pattern of SI across the conditions of the experiment also showed a significant difference depending on PAPR model. The SI performance rating for all PAPRs could meet the current NIOSH CBRN certification requirement for speech intelligibility.