Modeling generic dialog applications for embedded systems

A treatment system for reducing stuttering uses an auditory feedback modification technique to train the stutterer's speech motor control system to be more stable. The auditory feedback modification is based on a model of speech motor control in the human brain that incorporates a variation of observer-based control and Smith prediction. In addition, the Kalman gain of the model is set by comparing the speech muscular control signals sent to the person's vocal tract to the corresponding auditory speech sounds the person actually hears. It is believed that the speech motor control system of a stutterer has set the Kalman gain too high, thereby creating an unstable control system that in turn causes stuttering. A feedback modifier feeds back the stutterer's speech to the stutterer with a perturbation that is small enough to pass a validator function that is believed to be part of the speech motor control system. The small perturbations increase the difference between the target speech and the fed back speech, which is believed to cause the speech motor control system to decrease the Kalman gain. Over a treatment program, it is believed that the perturbations "train" or adapt the stutterer's speech motor control system so as to reduce the Kalman gain, which is further believed to persist when the auditory feedback is discontinued.

Presence of additive noise in speech signals deteriorates the performance of automatic speech recognition systems in cars. For a speech recognition system, we must know where speech and nonspeech segments are. In this paper a new Band Partitioning Spectral Entropy endpoint detection (BPSE) method is used to get the speech start and end point of speech precisely. After that Band Spectral Subtraction (BSS) methods provide in this paper can decrease additive noise obviously. Mel Frequency Cepstral Coefficients (MFCC) are extracted from segmented speech signals. The coefficients are recognized by Hidden Markov Model. The results show that the recognition accuracy can be improved from 39.3% to 95.5%.

Background : Ziegler (2003) reviews neural and behavioural evidence to support a task-dependent model of motor control, whereby motor speech disorders represent impairment of a sensory-minor system specialised for speech. Based on this approach, Ziegler argues against the examination of volitional or novel nonspeech motor activities to gain insight into motor control for speech. Aims : The primary objective of this paper is to discuss Ziegler's (2003) conceptualisation of the task-dependent model and present an alternative integrative model. In the latter, speech and volitional nonspeech motor control are integrated into the functioning of a more general motor system where neural and behavioural systems demonstrate areas of overlap. Studies of the nervous system, the evolutionary foundations of speech in great apes, behaviour, and motor learning are presented to support an integrative model of motor control. Main Contribution : Neurological and evolutionary evidence strongly suggest that neural networks are flexible, multifaceted, multifunctional and overlapping in function. It is highly likely that a higher-level behaviour like speech involves networks that are similarly multifunctional and overlapping with other motor functions. Ziegler's concept of task-dependent motor control may relate as much to parameters such as complexity, familiarity, and automaticity of task performance as to the nonpeech-speech distinction. Studies are reviewed that support the inclusion of nonspeech motor tasks in assessment of the disordered speech motor control system. Specific nonspeech tasks clearly facilitate differential diagnosis and provide insight into the functioning breakdown of the motor system for related but more complex speech behaviours. Finally, motor learing studies are discussed with particular reference to how these might inform models of motor control. Conclusions : This response cautions against the seemingly premature acceptance of a model assuming separate sensory motor systems for volitional nonspeech motor activities and speech. Continued research, without the limitations imposed by such an assumption, is required to enhance understanding of component parts of complex behaviours and how those components interact in normal and damaged systems at different levels of a performance. These data have the potential to form the basis for new, more effective approaches to treatment of motor speech disorders.

Survey on Deep Neural Networks in Speech and Vision Systems

The study aims to develop, theoretically substantiate, and pilot-test a hybrid educational model designed to foster clear and empathetic medical communication skills in medical students by integrating artificial intelligence tools (virtual patients, speech analysis systems) into the “Russian Language and Culture of Speech” course. The article examines the didactic potential of integrating simulators based on artificial intelligence (AI), virtual patients, and speech analysis systems to overcome the deficit of communicative practice in mass education settings. The authors provide a detailed analysis of the key components of the proposed hybrid model, including the use of adapted virtual patients for practicing typical and complex clinical scenarios within a Russian-speaking context; the application of precision speech and non-verbal behavior analysis systems for objective and instantaneous feedback; and the role of generative analytics and adaptive trajectories in personalizing the learning process. Particular attention is paid to the methodological integration of AI tools into the structure of the “Russian Language and Culture of Speech” course, including modular lesson design, the transformation of the teacher’s role, and ensuring synergy between technological and pedagogical components. The article also considers practical aspects of testing the model at the RUDN University and the Bolashaq Academy, identifying advantages and limitations, as well as ethical, legal, and infrastructural challenges associated with implementing AI in medical education. The scientific novelty lies in the development and theoretical substantiation of a hybrid educational model that ensures synergy between precision AI simulators (virtual patients, speech analysis systems) and the transformed role of the teacher (as a data analyst, mentor, and expert) within a humanities discipline during the early stages of medical education. As a result, a structural-functional hybrid model has been developed and theoretically substantiated. Pilot testing of the model’s elements revealed its didactic potential, evidenced by increased student motivation and engagement, as well as an increase in the number of training attempts. Key conditions and risks for successful implementation were established, including the need to create representative corpora of Russian-language medical dialogues, bridge the digital divide, and comply with ethical and legal norms.

Recently, the demand for the application of an Automatic Air Damper Control System in automobiles has been expanding. In this system; composed of one or two gas sensors and a signal processing software, it is important to detect incoming gasoline and diesel exhaust gases from other cars sensibly and reliably. However, conventionally used tin oxide (SnO2) based semiconductor gas sensors have high sensitivity to reducing gases (e.g. CO, HC) but are effected by the presence of oxidizing gases (e.g. NOX). Since the contents of reducing gas in diesel exhaust is relatively lower compared with gasoline exhaust, it is more difficult to detect diesel exhaust from low concentration ranges.

Summary Spoken language dialog systems allow users to control applications by voice. These systems tightly integrate the applications to control them, even though knowledge sources of the building blocks are often configurable. Some dialog systems controlling multiple applications loosen the coupling. This article introduces a dialog system accessing multiple applications with a dynamic setup that can be changed at run-time, separating the applications from the system. This is achieved by application-independent knowledge processing inside the dialog system based on modular ontological descriptions. A clear interface between dialog system and applications is provided, generic dialog functionality is realized on top of the application independent knowledge processing. Examples illustrate interactions with the system.

Speech is a natural form of interaction for people, and smart environments offer good possibilities for experimenting with new kinds of interaction with users and devices. Speech control can offer more intuitive and easy forms of interaction with the environment compared to traditional graphical or physical user interfaces. This paper describes the development, implementation and current ongoing work on a location-aware speech control and audio feedback user interface.

Problem: Issues related to increasing the performance characteristics of braking systems due to the use of car deceleration systems are considered. A structural analysis of car deceleration systems was performed according to a number of classification features: the system action mechanism; the principle of action and means of controlling the retarder; and the method of connecting the retarder brake. Ways of improving retarders based on the electrodynamic principle of construction are noted. The importance of improving the energy indicators of the pre-intermediate braking system due to the use of recuperative methods of self-sufficiency is emphasized. The Relevance of the study is determined by the increase in the number of motor vehicles involved in freight transportation in mountainous terrain. The Goal of the study is to improve the braking characteristics of the car's deceleration system under the conditions of a long descent. The research Methodology includes the improvement of the retarder design and the scheme of the braking force control system. Based on the results of the study, a classification structure of car deceleration systems was compiled; a qualitative analysis of the technical and operational characteristics of the generator-type electromagnetic retarder with axial magnetic flux was made; a technical solution for an electrodynamic retarder is proposed, which comprises two electric machines that provide a double-action braking moment, using recovered energy. The need for a quantitative assessment of the power balance of the double machine's components is identified, which allows optimization of the mass-dimensional indicators of the combined unit for the determined braking force of the deceleration system. Scientific Originality: The trend of transforming the composition of the power plant of a car with a passive electromagnetic retarder into a moderate and even full hybrid scheme is highlighted. The Practical Value of the research is demonstrated through recommendations that can be useful in the design of new systems and adaptation of existing deceleration systems of motor vehicles, which are mainly operated in mountainous terrain.

Design of an acceleration measurement system using a MEMS accelerometer to measure acceleration of automobiles in all the three axes is presented. Electronic stability control and anti-lock breaking systems in automobiles use the acceleration measurements to offer safety in driving. The system uses an ARM microcontroller to quantize the outputs of accelerometer and save the measurement data on a microSD card. A LabVIEW program has been developed to analyze the longitudinal acceleration measurement data and test the measurement system. Random noises generated and added with measurement data during measurement are filtered by a Kalman filter implemented in LabVIEW. Longitudinal velocity of the vehicle is computed from the measurement data and displayed on a graphical chart. Typical measurement of velocity of a vehicle at different accelerations and decelerations is presented.

Problem. This article addresses the issue of developing environmentally friendly vehicles and their electronic and electromechanical components. It provides an analytical review of advanced electromechanical technologies utilized in the creation of Tesla electric cars. Specifically, the study analyzes the electronic stability control system, active pneumatic suspension, and electric power steering. The perspective of electric cars lies in their ability to meet the economic requirements of modernity and align with the "Zero Emission" paradigm. The obtained results can serve as recommendations for the development of electronic and electromechanical systems and complexes of electric vehicles, benefiting scientific and technical professionals engaged in the creation of environmentally friendly vehicles. Goal. This study aims to analyze the advanced technologies used in the development of electronic and electromechanical systems of Tesla electric cars. Methodology. The research employs an analytical study of the characteristics of the electronic and electromechanical systems of Tesla electric cars to achieve the set goal. It includes a detailed analysis of the electronic stability control system, active pneumatic suspension, and electric power steering. Results. An analysis of scientific publications reveals that the problem of creating environmentally friendly and energy-efficient vehicles is currently being solved through the use of electric drives powered by traction batteries. Modern electric cars have overcome drawbacks such as low dynamics, limited range, and low maximum speed, surpassing similar internal combustion engine vehicles in these aspects. Tesla electric cars are currently the most technologically advanced and promising in this field. The analysis focuses on the technical solutions and advanced technologies employed in Tesla Model S electric cars, specifically the electronic stability control system, active pneumatic suspension, and electric power steering. The conducted research allows for an assessment of the current state of electronic and electromechanical systems in electric cars and provides insights into their future development. Originality. The results of this research provide a comprehensive understanding of the present state of electronic and electromechanical systems in Tesla electric cars. It enables a detailed analysis and exploration of the advanced technologies used in the development of Tesla electric cars and their distinctive features. Practical Value. The research findings contribute to identifying promising directions for the development of contemporary electronic and electromechanical systems in electric vehicles. They serve as a basis for creating recommendations concerning electronic stability control systems, active pneumatic suspension, and electric power steering, which can be valuable to scientific and technical professionals involved in the development of environmentally friendly vehicles.

Globally, a common trouble is the inefficiency of security systems in cars, several vehicles are stolen for this reason every year. The purpose on this paper is to make an embedded system for vehicular security. This system has direct communication with a smartphone, adding some control systems manipulated by user. It has an electronic card, as embedded system, that makes communication work, control, data process and voltage source. The system has microcontrollers and satellite communication modules to improve its communication characteristics, making high efficiency. This way, we look to do a social work in the local area to prevent and recover vehicles with this trouble.

With the rapid development of computer network applications and the growing popularity of computer technology, computer network remote control technology widely used.Users unrestricted geographical conditions, different locations via the network control network devices, network devices to obtain information.Remote control technology greatly facilitates network maintenance and control, has a very important value.According to this trend, the paper computer network remote control technology research.

ABSTRACTGesture control systems based on mid-air haptics are increasingly used in infotainment systems in cars, where they can provide rich haptic feedback to improve human-computer interactions. Laboratory studies show that mid-air haptic feedback reduces drivers’ distractions and improve safety. However, it is unclear how the perception of mid-air ultrasound stimuli is affected by prolonged exposure to vibrational noise, e.g., from the steering wheel of a moving vehicle. Studies on vibrotactile adaptation show that perception of mechanical vibration is impaired by prior exposure to stimuli of the same frequency. Here, we investigated the effect of mechanical adaptation on the perception of mid-air ultrasound stimuli. We measured participants’ detection threshold for ultrasound stimuli of different frequencies both before and after exposure to 30 s mechanical vibrations. Across two experiments, we systematically manipulated the frequency and amplitude of the adapting stimulus. We found that exposure to low-frequency mechanical vibrations significantly impaired the detection of low-frequency ultrasound stimuli. In contrast, exposure to high-frequency mechanical vibrations equally impaired perception of both low- and high-frequency ultrasound stimuli. This effect was mediated by the amplitude of the adapting stimulus, with stronger mechanical vibrations producing a larger increase in participants’ detection threshold. Overall, these findings show that perception of mid-air ultrasound stimuli is affected by specific sources of mechanical noise. Crucially, frequency-specificity in the low-frequency band also points toward possible mitigating solutions that could help minimising unwanted desensitization of mechanoreceptor channels during mid-air haptic interactions.

Control model is important to performance of automobile anti-collision control system. This work brought out a fuzzy control model for automobile longitudinal anti-collision system. Considering distinct running conditions of front vehicle, the mathematical model for safety distance calculating was constructed. After given the fuzzy controller model and algorithm, it designed the physics system of anti-collision control. By simulation with LabView and MATLAB, the fuzzy control based on the model considered conditions of front vehicle is proved to agree with real traffic condition.