Car Horn Research Articles

Enhancing Situational Awareness with VAS-Compass Net for the Recognition of Directional Vehicle Alert Sounds.

People with hearing impairments often face increased risks related to traffic accidents due to their reduced ability to perceive surrounding sounds. Given the cost and usage limitations of traditional hearing aids and cochlear implants, this study aims to develop a sound alert assistance system (SAAS) to enhance situational awareness and improve travel safety for people with hearing impairments. We proposed the VAS-Compass Net (Vehicle Alert Sound-Compass Net), which integrates three lightweight convolutional neural networks: EfficientNet-lite0, MobileNetV3-Small, and GhostNet. Through employing a fuzzy ranking ensemble technique, our proposed model can identify different categories of vehicle alert sounds and directions of sound sources on an edge computing device. The experimental dataset consisted of images derived from the sounds of approaching police cars, ambulances, fire trucks, and car horns from various directions. The audio signals were converted into spectrogram images and Mel-frequency cepstral coefficient images, and they were fused into a complete image using image stitching techniques. We successfully deployed our proposed model on a Raspberry Pi 5 microcomputer, paired with a customized smartwatch to realize an SAAS. Our experimental results demonstrated that VAS-Compass Net achieved an accuracy of 84.38% based on server-based computing and an accuracy of 83.01% based on edge computing. Our proposed SAAS has the potential to significantly enhance the situational awareness, alertness, and safety of people with hearing impairments on the road.

FUNGSI MUSIK KALASON OTO SEBAGAI HIBURAN DALAM BUDAYA TRANSPORTASI MASYARAKAT SUMATRA BARAT

In this research, the author uses the concept of music function from Alan P. Meriam. After understanding the problem of the function of music contained in oto kalason (literally: car horn), from this concept, it can be explained that oto kalason functioned as the only entertainment in West Sumatran society at that time (especially when traveling by bus), both inside traveling by oto-oto (buses) at that time, or in people's daily activities. The horns on public transport buses at that time could play songs, sing, even the profession of being a car horn player was quite promising at that time. This horn sound is what many people have been waiting for, a sound that is loved by many people. This is a genre that has long colored the lives of the people of West Sumatra and the transportation (buses) of that time.

Recognition of car horns based on principal component analysis of MEL frequency Cepstral coefficients and support vector machine

With the rapid increase in the number of automobiles, the noise pollution caused by car horns is attracting more attention. In order to accurately identify car horn sounds in traffic noise and strengthen traffic law enforcement, research on car horn sound recognition is becoming increasingly important. In this paper, using Principal Component Analysis (PCA) to optimize and reduce the dimensionality of extracted Mel Frequency Cepstral Coefficients (MFCC), feature vectors are input into four models: Support Vector Machine (SVM), Back Propagation (BP) Neural Network, Extreme Learning Machine (ELM), and Random Forest (RF). These models are utilized to classify and identify car horn sounds from traffic noise. The impact of feature dimensions and Signal-to-noise ratio(SNR) on recognition performance is analyzed. The results show that under this method, the recognition rates of the four models can be increased by increasing the number of Mel filters and feature dimensions in MFCC, which can improve recognition performance, especially when the SNR is lower. The SVM model exhibits the most significant improvement in recognition rate. They achieve the best recognition rates for measured car horn sounds of 98.66 %, 93.98 %, 89.44 %, and 95.12 %, respectively. Experimental results demonstrate that the proposed method has good recognition performance and can be effectively applied to the supervision of car horn usage on actual roads.

Tailored for vehicle horn: A novel sound source capture method

The development of a horn sound capture system, capable of replacing manual control, offers a promising solution for alleviating horn noise. Existing horn sound systems lack localization algorithms that are capable of robustly resisting interference. To address this issue, this paper introduces an innovative horn sound capture system, including hardware and algorithms for sound recognition and localization. The pivotal innovation of the system is the introduction of the Sub-SRP algorithm, an advancement of the steered-response power phase transform (SRP-PHAT). Leveraging the frequency characteristics of horn sounds, it employs a series of filtering and spectral subtraction techniques to effectively filter out non-horn noise sources. In the interference experiment and field test, the Sub-SRP algorithm achieved DOA scores of 0.96 and 0.95, respectively, showing an approximately 10% improvement compared to the existing weighted SRP-PHAT, this improvement is even more pronounced under strong interference, increasing to 17%. This improvement significantly enhances the system’s ability to accurately capture honking vehicles and resist interference. Additionally, the horn sound recognition algorithm achieved accuracy rates of 95.75% and 97.65% in the two experiments, demonstrating the system’s effectiveness. In summary, this study contributes to the advancement of urban noise management and intelligent noise control systems.

Vibe - With people with hearing impairment

Hearing loss significantly impacts daily life, leading to communication difficulties, social isolation, and increased risk of accidents. This can cause frustration, anxiety, and depression. The use of sound indication devices improve the quality of life for individuals with hearing impairment by providing them with a means to detect sounds in their environment. We have developed Vibe, a device that alerts a user to specific sounds (a baby's cry, an alarm, a door knock, a vehicle horn, or a spoken name) in their environment. Our device uses EdgeML, a form of machine learning, to perform tasks locally on the device rather than relying on cloud-based services. This approach has the advantage of reduced latency and improved privacy. The EdgeML model was trained on a locally collected dataset, for better applicability to the Indian environment. Devices such as Vibe will help individuals with hearing impairment navigate their surroundings safely and confidently, leading to increased independence and improved mental health.

Auditory impression of amplitude-modulated vehicle horn sounds and their detectability in noisy environment

Vehicle horn sounds, due to their high sound pressure levels, induce negative psychological reactions in listeners, especially pedestrians. In order to reduce such negative effects, a horn sound with a lower sound pressure level is desired. At the same time, a horn sound should be easily perceived by drivers, considering its use on busy roads. The amplitude-modulated horn sound may help to solve these problems. Therefore, we synthesized amplitude-modulated horn sounds, and conducted psychoacoustical experiments to investigate the relationship between the acoustic characteristics and the perceived quality of these sounds. The results showed that stimuli with shallower modulation depths were less unpleasant than those with deeper modulation depths, and stimuli with modulation frequencies below 40 Hz suppressed auditory unpleasantness more than those with higher modulation frequencies. To confirm their effectiveness for detection in noisy conditions, stimuli with different signal-to-noise ratios were created by combining the amplitude-modulated horn sound and road traffic noise. The amplitude-modulated horn sound in road traffic noise was detected even in conditions where the signal-to-noise ratio was 3 dB lower than when the horn sound was not amplitude-modulated. The results indicate that amplitude-modulated horn sounds have the potential to improve the sound environment around roads.

TWO-WHEELED MOTORIZED VEHICLE SECURITY USING E-KTP

Motor vehicle theft from year to year always increases, both when parked and while being driven. Data from the National Police Headquarters for the period 1 to 7 May 2022 recorded 118 cases, and increased to 309 cases in the period 8 May to 14 May 2022. Based on the problem with the increase in motorized vehicle theft, a system is needed that can protect motorized vehicles from these theft cases. In this article we propose an additional system for electronic motorized vehicles. This system consists of additional controls, namely an e-KTP and touch screen, while the switch for the front brake already exists in motorized vehicles. After the ignition is turned on, the driver must press the touch screen button, press the front brake, attach the e-KTP to the RFId reader, each maximum time span for 50 seconds. If it is not in the sequence and the time is more than 50 seconds it will cause the motorized vehicle's horn to sound. After connecting, making controls and testing, the control system can work perfectly..

Assessment of Noise Pollution Levels at Major Motor Parks in Port Harcourt Metropolis, Rivers State, Nigeria

Two motor parks in Port Harcourt had their noise pollution levels examined. The motor parks at Waterlines and at Rumuokoro are among the busiest in the city and have a lot of nearby sources of noise. The relative humidity and temperature meters were used to measure the relative humidity and the temperature at the parks, respectively. The sound level meter was used to measure sound levels. A questionnaire was provided to 63 respondents (38 at Rumuokoro motor park and 25 at Waterlines based on willingness to participate) in order to get subjective data. Statistical Package for Social Science (SPSS) version 20 was used to compute the noise descriptors. Pearson correlation was employed to assess the link between the measured dependent variable (noise level) and the independent variables (temperature, humidity, wind speed and wind direction). Results show that both motor parks have similar noise sources. The identified noise sources were loudspeakers from music shops, car engines, car horns, power generators, loud arguments, and advertising of products by vendors and hawkers. Additionally, preachers with megaphones and vulcanizers were found at Rumuokoro automobile park. In Waterlines motor park, the lowest and highest noise levels were 51.0 and 73.1 dBA, while it was 52.1 and 83.3 dBA in Rumuokoro motor park. The respondent's knowledge of noise's health effects was considered. While most respondents acknowledged that high noise levels affect work productivity and cause hearing problems, most rejected that high noise levels affected their communication and sleep. This shows that noise pollution and its effects on physical, social, and psychological health require better education.

Adaptive Noise Reduction Algorithm Based on SPP and NMF for Environmental Sound Event Recognition under Low-SNR Conditions

Nonnegative matrix factorization- (NMF-) based noise reduction methods can effectively improve the performance of environmental sound recognition. However, when the environmental sound overlaps highly with the noise, the spectral line loss and noise residue will occur in the low signal-to-noise ratio (SNR) condition. An adaptive noise reduction algorithm was proposed in this paper. First, noisy environmental sound is separated into estimated noise and environmental sound using NMF. Then, the estimated noise is used to calculate sound presence probability (SPP), which is adapted to decrease spectral line loss and achieve accurately estimated noise. Subsequently, the estimated noise combines with noisy environmental sound to obtain the estimated environmental sound. Finally, SPP is applied to reduce residual noise in the estimated environmental sound and reconstruct the environmental sound. The simulation results demonstrate that the proposed algorithm outperforms the traditional algorithms and NMF-based methods in terms of perceptual evaluation of speech quality (PESQ) and global SNR with increase of X% and X%, respectively. Moreover, the proposed method can effectively improve the environmental sound recognition rate. Particularly, the proposed method makes a 16.2% increase of F1-score in car horn recognition under the realistic acoustic condition.

청각장애인을 위한 인공지능 헤드폰 설계

We designed an artificial intelligence (AI) headphone for hearing impaired people and proposed a convolution neural network (CNN)-based sound classifier with a low computational network that can run on an embedded PC (Raspberry Pi 4B) in real-time. Because our AI headphone can classify 20 types of dangerous or environmental sounds (e.g., siren, car horn, scream, gunshot, etc.) and recognize specific voice keywords (e.g., person name, be careful!, stop!, etc.), it can assist hearing impaired people in reducing the risk of accident exposure and improving convenience. In addition, we use vibration codes to notify the hearing impaired person of detected information to the vibration motors attached to both sides of the headphone. We confirm that our proposed sound classifier achieves an average accuracy rate of approximately 95.14%, and enables real-time processing on the Raspberry Pi 4B because it requires an average computation time of approximately 0.139s with audio recording data for 5.12s.

Andrzej Bobkowski and Józef Czapski

Andrzej Bobkowski and Józef Czapski

Exhibition Review: Tuan Andrew Nguyen: Unburied Sounds

Exhibition Review: <i>Tuan Andrew Nguyen: Unburied Sounds</i>

Hearing aid solutions for children with autism

Children with the autistic spectral disorder (ASD) have difficulty processing sensory inputs, especially auditory inputs. There have been a number of technological solutions that have developed based on different approaches in the form of hearing devices, however, limitations include the inability to successfully allow, through whitelisting, important sounds such as fire alarms and the sounds of cars and car horns. This paper proposes a hearing device supported by an application as a solution for children with ASD, the device is based on blacklisting and whitelisting features that allow for a reduction in auditory input through a selective process and contributes to selectivity through whitelisting for safety purposes. The proposed device will reduce distraction associated with hyper-responsiveness to certain auditory inputs, such as those from teachers or working group members, and increase concentration in the child by having fewer distractions.

THE STUDENTS' MOTIVATION IN LEARNING ENGLISH FROM HOME AT SMA NEGERI 3 LUWU

This study aimed to determine The Students' Motivation in Learning English From Home. The method of this research was the descriptive qualitative method. Data for the research was collected through interviews (semi-structured interviews) with WhatsApp (WA) as a data collection tool.The sample for this research was students of class XI IPA SMA Negeri 3 Luwu. Samples were taken using the purposive sampling technique.Based on the results of the study, the researchers found that learning English from home makes students tend to be lazy and their learning motivation decreases because it is influenced by extrinsic motivation, such as the environment, teachers, and parents.In the environment part, conditions at home cause a lot of disturbances when starting the lesson, whether it's the sound of chickens, television, car horns, or the sound of motorcycles that interfere.In the teacher part, the teacher is an important factor in aspiring for the implementation of these functions by meeting the needs of students. These needs include physiological needs, the need for safety and security, the need to be accepted and loved, the need for self-esteem, and the need for self-realization.In the parents part, lack of parental attention when studying from home means that learning interest is reduced. Parents who are busy with their work make their children feel neglected. This condition certainly requires parents and families to accompany children, especially in the learning process. The active role of parents and families in children's education, especially during the pandemic, is very important, especially since the role of teachers and educational institutions is more limited in scope. There is a very close and significant relationship between online learning and student learning motivation. Learning motivation was very influential on learning from home.

End-to-End Train Horn Detection for Railway Transit Safety.

The train horn sound is an active audible warning signal used for warning commuters and railway employees of the oncoming train(s), assuring a smooth operation and traffic safety, especially at barrier-free crossings. This work studies deep learning-based approaches to develop a system providing the early detection of train arrival based on the recognition of train horn sounds from the traffic soundscape. A custom dataset of train horn sounds, car horn sounds, and traffic noises is developed to conduct experiments and analysis. We propose a novel two-stream end-to-end CNN model (i.e., THD-RawNet), which combines two approaches of feature extraction from raw audio waveforms, for audio classification in train horn detection (THD). Besides a stream with a sequential one-dimensional CNN (1D-CNN) as in existing sound classification works, we propose to utilize multiple 1D-CNN branches to process raw waves in different temporal resolutions to extract an image-like representation for the 2D-CNN classification part. Our experiment results and comparative analysis have proved the effectiveness of the proposed two-stream network and the method of combining features extracted in multiple temporal resolutions. The THD-RawNet obtained better accuracies and robustness compared to those of baseline models trained on either raw audio or handcrafted features, in which at the input size of one second the network yielded an accuracy of 95.11% for testing data in normal traffic conditions and remained above a 93% accuracy for the considerable noisy condition of-10 dB SNR. The proposed THD system can be integrated into the smart railway crossing systems, private cars, and self-driving cars to improve railway transit safety.

Analysis of the Effects and Causes of Driver Horn Use on the Acoustic Environment at Urban Intersections in Taiwan

Car horns were originally installed in vehicles for safety. However, many urban areas in several countries face noise problems related to the use of car and motorbike horns. To propose measures to suppress the use of horns, relationships between horn use and factors including driver awareness and behavior, traffic environment, and the transportation system should be investigated. The present study therefore conducted surveys to grasp the current circumstances of horn use and traffic at urban intersections in Taiwan. The relationship between horn use and the traffic volume of standard-sized vehicles was found. According to an analysis of horn use during traffic signal cycles, in many cases, horns were honked after entering intersections to turn left. In particular, horns were honked when the driver waited more than 4 s for the car in front to start moving after the green light allowing left turns was turned on. An analysis of noise levels at intersections showed that the maximum noise level value (LAmax) could be reduced if vehicle horns were not used. Multiple regression analysis also indicated that LAmax values increased with the frequency of horn use. The equivalent continuous A-weighted sound pressure level (LAeq,10min) did not change with driver horn use, and increased with the traffic volume of motorcycles.

Extrinsic Motivation of Students at SMA Negeri 3 Luwu to Learn English from Home

This study used qualitative research that consisted of ten students from senior high school in Luwu. To determine the extrinsic motivation when the students learn from home, the students answered the interview that consisted of ten items. The study discovered that learning English at home makes children sluggish and that their drive to learn lowers due to their surroundings, teachers, and parents. On the environmental side, disruptions at home, such as the sound of chickens, televisions, car horns, or the unsettling sounds of motorcycles, are common when beginning lessons. On the teacher's side, most teachers give students assignments without thoroughly explaining the material, causing students to be sluggish about taking home lessons, particularly in English subjects. Because they are lazy, teachers are ineffective at carrying out their responsibilities by satisfying the needs of children. Physiological demands, the market to be accepted and loved, the need for self-esteem, and the need for self-realization are all examples. When studying at home, their children's interest in learning is stifled by the lack of parental attention. Children feel abandoned when their parents are preoccupied with their professions. Parents and families must be there for this condition, especially during the learning period. The necessity of parents and families to participate actively in their children's education is vital, especially during a pandemic when teachers and educational facilities are restricted.

Frequency-Dependent Plasticity in the Temporal Association Cortex Originates from the Primary Auditory Cortex, and Is Modified by the Secondary Auditory Cortex and the Medial Geniculate Body.

The brain areas that mediate the formation of auditory threat memory and perceptual decisions remain uncertain to date. Candidates include the primary (A1) and secondary (A2) auditory cortex, the medial division of the medial geniculate body (MGm), amygdala, and the temporal association cortex. We used chemogenetic and optogenetic manipulations with in vivo and in vitro patch-clamp recordings to assess the roles of these brain regions in threat memory learning in female mice. We found that conditioned sound (CS) frequency-dependent plasticity resulted in the formation of auditory threat memory in the temporal association cortex. This neural correlated auditory threat memory depended on CS frequency information from A1 glutamatergic subthreshold monosynaptic inputs, CS lateral inhibition from A2 glutamatergic disynaptic inputs, and non-frequency-specific facilitation from MGm glutamatergic monosynaptic inputs. These results indicate that the A2 and MGm work together in an inhibitory-facilitative role.SIGNIFICANCE STATEMENT: The ability to recognize specific sounds to avoid predators or seek prey is a useful survival tool. Improving this ability through experiential learning is an added advantage requiring neural plasticity. As an example, humans must learn to distinguish the sound of a car horn, and thus avoid oncoming traffic. Our research discovered that the temporal association cortex can encode this kind of auditory information through tonal receptive field plasticity. In addition, the results revealed the underlying synaptic mechanisms of this process. These results extended our understanding of how meaningful auditory information is processed in an animal's brain.

City Profile: Dakar

City Profile:Dakar J. R. Patterson (bio) Léopold Sédar Senghor The Collected Poems Trans. Melvin Dixon University of Virginia Press Mariama Bâ So Long a Letter Trans. Modupé Bodé-Thomas Waveland Press David Diop At Night All Blood Is Black Trans. Anna Moschovakis Farrar, Straus and Giroux Boubacar Boris Diop Doomi Golo—The Hidden Notebooks Trans. Vera Wülfing-Leckie & El Hadji Moustapha Diop Michigan State University Press Anna Badkhen Fisherman’s Blues: A West African Community at Sea Riverhead Books 2022 NEUSTADT PRIZE LAUREATE! Click for larger view View full resolution “AFRICAN RENAISSANCE MONUMENT” BY PENNSTATENEWS IS LICENSED UNDER CC BY-NC-ND 2.0 LIKE A PILLOW that has burst its seams, Dakar overflows with an excess of life. The resultant drift of people, goods, and animals through the city is a raucous cacophony of metal and flesh. Initiating it, it seems, are the shopkeepers, who, egged on by some madness, empty their stores to display their wares on the sidewalks, if not the street itself. Pedestrians and aimless livestock, thus displaced, wander itinerant through busy intersections as one would an open plain. Drivers take it all in stride, using this stricture as an opportunity to free themselves from the burdens of direction and signage. The result is a pandemonium of travel, a melee of feet, wheels, and hooves. The klaxon is the lingua franca, a beep available for every expression from “Here I am!” to “Whee! I’m driving!” to “I don’t brake for children.” The gumming of Dakar’s arterial flow can be overwhelming; if one finds the car horn one of the world’s lesser languages, it is downright oppressive. Above the fracas, on a scrubby hillock, rise the emblematic threesome of a beefy man, his zaftig wife, and their pointing babe: the African Renaissance Monument, the tallest statue on the continent. The North Korean–built monolith is either, depending on one’s view, an embodiment of African rebirth and self-empowerment or a vanity project and cash cow for former president Abdoulaye Wade. Either way, it is impressively large, an imposing image of a pert, muscular family. Cities are not only formed of their brutish reality but also the collective ideas of their residents. This is fortunate for Dakar, a cornucopia of ideas and vision, where literature plays an important characterizing role. The most famous character is undoubtedly Léopold Sédar Senghor, who, elected as independent Senegal’s first president in 1960, was an acclaimed poet before his political rise, a model of Mao’s pen-and-sword ideal of a ruler. On the opposing side, his political rival, historian Cheikh Anta Diop, wrote a litany of intellectual publications that gave rise to Pan-Africanism and “Diopian thought.” Their joint struggle against oppression made Dakar one of the cradles of Négritude. Though Senghor and Diop, like Cheikh Hamidou Kane, are authors of another time, their themes of displacement and rebirth have carried through to today. The 2021 International Booker Prize went to the French-Senegalese author David Diop and translator Anna Moschovakis for At Night All Blood Is Black, which follows a Senegalese man into the fracas of the Second World War. That war casts a surprisingly heavy shadow over western Africa; war-grave cemeteries are found throughout this part of the continent. Dakar’s—Bel Air Cemetery—is near the sea, half a mile from the Museum of Black Civilization. Another everlasting theme is the troubled relationship between France and Senegal, between Dakar and Paris; two large, powerful countries within their respective spheres of influence, inextricably linked through history and language. This bond marks the work of authors Fatou Diome and Ndèye Fatou Kane, and filmmaker Ous-mane Sembène. There are, of course, other languages; both indigenous and widely spoken: Wolof, Pulaar, Sere, and Diola, to name a few. Books in these languages are rare to nonexistent, though the established writer and 2022 Neustadt Prize laureate, Boubacar Boris Diop, for one, writes in Wolof. When moving about the city, avoid, if possible, the cacophony of Sicap-Liberté and Grand Yoff arrondissements, where zones like S.C.A.T. live up well to their acronym. Stick to...

Comparative evaluation of different steel for mobile nucleus of electromechanical disc type vehicle horn

A horn is a sound making device of the motor vehicle, which plays an important role for the improvement of safety. A disk type electro-mechanical horn considered in this paper utilize a complex system of electro-magnetic coils, contacts, springs and diaphragm all connected through a shaft known as mobile nucleus. Fixed nucleus is the counter part of mobile nucleus, which remains steady during application. The vibrating system and the electromagnetic system are the part of the horn and they interact through a circuit breaker, which actuated by very high frequency (300–500 cycle/second) motion of the mobile nucleus. Finally, there is an acoustic system, which aims at transforming the mechanical energy of vibrations into acoustic energy. Due to such high frequency working condition, mechanical actuators used in these devices have certain limitations and are prone to mechanical failure. Diaphragm and nucleus out of all parts considered critical. Nucleus will be continuously under high frequency fatigue, fretting fatigue with assembly and continuous impact/wear and tear with fixed nucleus. The selection of material within the interaction between the vibrating system and the electromagnetic field is useful for designing new efficient horns. Therefore, the present paper focuses on the selection of steel for mobile nucleus for longer life cycles / duration. In present paper discussing the comparative evaluation (Microstructure, Inclusion analysis, Micro hardness and Product level test failure analysis etc.) of two different mobile nucleus steel having medium (EN8D) and low carbon (C1010) were studied. The results showing that the use of medium carbon steel as an effective mobile nucleus material in electromechanical horn is superior with required fatigue properties.