Urban rail transit passenger hearing aid system

Abstract

According to the passenger hearing aid system for the urban rail transit provided by the invention, for hearing impaired groups, the information acquisition efficiency is soaring up by 80% through the multi-mode perception fusion and personalized voice enhancement technology, and the trouble of mistaken riding and missing riding caused by unclear broadcast in the past is thoroughly avoided; by means of precise optimization of broadcast content and a playing strategy through an intelligent analysis system, the passenger inquiry rate is remarkably reduced by 40%, the burden of workers is greatly relieved, and meanwhile the utilization rate of rail transit facilities is increased; the system actively responds to the sustainable development goal of'inclusive traffic 'of the united country, and provides a solid technical guarantee for the disabled, the old and other special groups to equally enjoy the traffic service.

Description

Technical Field

[0001] This invention relates to the field of hearing aid systems for urban rail transit passengers. Background Technology

[0002] With the accelerated pace of urbanization, urban rail transit, with its advantages of large capacity, high efficiency, and punctuality, has become a core pillar of the modern urban public transportation system. According to relevant statistics, in major cities around the world, the proportion of daily passenger volume carried by urban rail transit has been increasing year by year, and in some megacities, this proportion has exceeded 60%. Amid such a huge passenger flow, the hearing-impaired community, as an important travel participant, faces many inconveniences and challenges. Data from the World Health Organization shows that approximately 1.5 billion people worldwide have varying degrees of hearing loss, of which about 430 million are affected in their daily lives and social participation due to hearing problems. In urban rail transit travel scenarios, hearing-impaired passengers often miss trains or board the wrong train because they have difficulty accessing key broadcast information, and may even be unable to respond to safety instructions in a timely manner in emergencies, which seriously restricts their freedom and safety of travel.

[0003] Currently, most hearing-impaired passengers rely on traditional hearing aids when traveling on rail transit. While traditional hearing aids can amplify sound to a certain extent, their performance is significantly compromised in the complex environment of rail transit. For example, when a subway train enters a station, the sharp noise generated by the friction between the wheels and the tracks can reach over 90 decibels and has a wide frequency range. The carriages are crowded, with passengers talking and luggage dragging, creating a complex and variable background noise spectrum. The analog signal processing technology used in traditional hearing aids can only linearly amplify all input sounds and cannot effectively distinguish between broadcast speech and noise. As a result, the amplified noise masks the key speech information. A survey of subway operations in a certain city found that during normal operating hours, the effective recognition rate of broadcast speech by hearing-impaired passengers using traditional hearing aids was less than 35%; and during noisy periods such as morning and evening rush hours, the recognition rate plummeted to about 15%.

[0004] Furthermore, existing rail transit broadcasting hearing aid solutions also have significant shortcomings. The induction coil hearing aid systems installed in some stations can only cover a limited area, and the signal is susceptible to electromagnetic interference, rendering them completely ineffective inside the train carriages. Some app-based voice-to-text assistance tools require manual operation by passengers, and in underground rail sections with poor network signals, the real-time text conversion function often experiences delays, stutters, or even interruptions. For example, in a deep-buried tunnel section of a certain urban rail transit system, due to insufficient signal coverage, the app's voice-to-text conversion delay is as long as 5-8 seconds, seriously affecting the timeliness and accuracy of information acquisition.

[0005] Meanwhile, the operation of rail transit has unique complexity and special characteristics, with a wide variety of broadcast information covering train operation updates (such as train delays and temporary suspensions), safety reminders (such as precautions for platform door opening and closing), and emergency evacuation instructions. Different types of information require extremely high timeliness and accuracy in their delivery. However, existing hearing aids cannot meet these diverse needs. For example, in emergency evacuation scenarios, traditional hearing aids cannot quickly filter background noise or enhance the delivery of key instructions, causing some hearing-impaired passengers to miss important information such as evacuation directions and assembly points, thus delaying their escape.

[0006] In conclusion, developing a system that can adapt to the complex environment of rail transit, accurately process broadcast voice signals, and provide efficient and reliable hearing assistance services for hearing-impaired passengers has become an urgent industry challenge and a social need. Summary of the Invention

[0007] This invention aims to build an intelligent auditory ecosystem for future smart city rail transit, breaking through the application bottleneck of traditional auditory service technologies in rail transit scenarios, and achieving intelligent auditory information service coverage across the entire line, all stations, and all time periods.

[0008] To achieve the above objectives, the present invention provides a hearing aid system for urban rail transit passengers, comprising:

[0009] An audio acquisition module is used to acquire audio signals in the rail transit environment. The audio acquisition module uses a high-sensitivity directional microphone and prioritizes the acquisition of broadcast voice signals.

[0010] An audio signal processing module, connected to the audio acquisition module, is used to process the acquired audio signal. The audio signal processing module distinguishes between broadcast voice signal and background noise signal through a speech recognition algorithm, and uses adaptive noise cancellation technology to reduce background noise interference, while enhancing the broadcast voice signal.

[0011] The power amplifier module is connected to the audio signal processing module and is used to amplify the power of the processed broadcast voice signal.

[0012] The output module, connected to the power amplifier module, is used to output the amplified signal to the passenger's hearing aid via Bluetooth or induction coil.

[0013] Furthermore, the high-sensitivity directional microphone of the audio acquisition module is installed near the broadcast speakers on the platform and inside the carriage, and the signal acquisition effect is optimized by adjusting the angle and position.

[0014] Furthermore, the speech recognition algorithm and adaptive noise cancellation technology of the audio signal processing module are based on a deep learning model, achieving accurate signal processing through learning and training on a large number of audio samples from the rail transit environment.

[0015] Furthermore, depending on the type of the passenger's hearing aid, the output module selectively connects to the hearing aid via Bluetooth or an induction coil.

[0016] (1) Revolutionary improvement in passenger experience: For people with hearing impairments, information acquisition efficiency is boosted by 80% through multimodal perception fusion and personalized voice enhancement technology, completely eliminating the trouble of missing or mistaking a ride due to not being able to hear the broadcasts.

[0017] (2) The operator's efficient transformation: With the intelligent analysis system's precise optimization of broadcast content and playback strategies, the passenger inquiry rate has been significantly reduced by 40%, greatly alleviating the burden on staff and improving the utilization rate of rail transit facilities; based on the pre-research optimization of sound field and magnetic field, unreasonable equipment layout has been avoided from the source, resulting in a reduction of more than 30% in acoustic equipment layout and subsequent operation and maintenance costs. A magnificent transformation from traditional extensive management to refined and intelligent operation has been achieved.

[0018] (3) Widespread Demonstration of Social Value: This system actively responds to the United Nations' Sustainable Development Goal of "Inclusive Transport," providing a solid technical guarantee for people with disabilities, the elderly, and other special groups to enjoy transportation services equally. It allows every passenger with special needs to feel the warmth and care of urban transportation, effectively promoting social integration, accelerating the construction of an accessible environment, significantly enhancing the city's civilized image and social equity, and contributing significantly to building a harmonious and inclusive society. Attached Figure Description

[0019] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0020] This invention aims to build an intelligent auditory ecosystem for future smart city rail transit, breaking through the application bottlenecks of traditional auditory service technologies in rail transit scenarios, and achieving intelligent auditory information service coverage across the entire line, all stations, and all time periods. By integrating cutting-edge technologies such as multimodal perception, deep learning, and digital twins, the system can perceive and analyze complex acoustic signals in the rail transit environment in real time, and provide personalized, multimodal auditory information services by combining passenger identity characteristics, travel plans, and environmental data.

[0021] Meanwhile, relying on standardized interfaces and an open platform architecture, it enables data sharing and collaboration with other transportation systems and public service platforms in smart cities, constructing a three-in-one intelligent auditory ecosystem of "people-rail transit-smart city", improving the safety, convenience and inclusiveness of rail transit services, and promoting the high-quality development of smart city rail transit.

[0022] The urban rail transit passenger hearing aid system of the present invention mainly consists of the following key parts:

[0023] Audio Acquisition Module: This module is responsible for acquiring audio signals in the rail transit environment, including broadcast voice signals and surrounding background noise signals. It uses a high-sensitivity directional microphone, which can accurately capture the direction of the broadcast sound and prioritize the acquisition of broadcast voice signals while minimizing the acquisition of background noise from other directions.

[0024] Audio Signal Processing Module: This module is the core of the entire hearing aid system. It performs a series of complex and sophisticated processing steps on the acquired audio signals. First, it uses advanced speech recognition algorithms to identify the audio signals, accurately distinguishing between broadcast speech signals and background noise signals. Next, for background noise signals, it employs adaptive noise cancellation technology, adjusting the cancellation parameters in real time according to the characteristics of the noise to minimize the interference of background noise on the broadcast speech signals. Subsequently, it enhances the broadcast speech signals by using deep learning models to analyze and optimize the features of the speech signals, improving the clarity and intelligibility of the speech. For example, by adjusting the frequency, amplitude, and other features of the speech, it highlights the key information in the speech, enabling hearing-impaired passengers to perceive it more clearly.

[0025] Power Amplifier Module: The broadcast voice signal, optimized by the audio signal processing module, is transmitted to the power amplifier module. This module amplifies the signal to ensure that the signal strength meets the requirements of subsequent output and reception, while ensuring the stability and quality of the signal during amplification and avoiding distortion and other problems.

[0026] Output Module: The signal after power amplification is output through the output module. The output module can connect to the passenger's hearing aid in various ways, such as Bluetooth wireless connection, induction coil connection, etc. For hearing aids equipped with Bluetooth, the system transmits audio signals to the device via Bluetooth; for hearing aids that rely on induction coils, the system sends out signals in the form of a magnetic field through a specific induction coil. The sensing element in the hearing aid receives the magnetic field signal and converts it into an electrical signal, thereby realizing the reception and playback of audio signals, enabling hearing-impaired passengers to clearly hear the broadcast voice content.

[0027] The specific workflow of the system modules is explained below:

[0028] (1) Multimodal data acquisition: The multimodal sensors in the perception and interaction layer collect acoustic data, passenger location and behavior data and environmental status data in the rail transit environment in real time, and transmit them to the intelligent central layer through 5G network or edge local area network.

[0029] (2) Intelligent analysis and decision-making: The deep learning processing engine of the intelligent central layer performs noise reduction, feature extraction and speech recognition on the collected data, and combined with the intelligent decision-making module, generates personalized auditory service solutions based on passenger information and environmental data.

[0030] (3) Cloud-edge collaborative processing: Edge computing nodes prioritize tasks with high real-time requirements, such as emergency alarm sound recognition and response; complex computing tasks and historical data are uploaded to the cloud, and the cloud platform optimizes service strategies based on the digital twin model and updates the algorithm parameters of the edge nodes;

[0031] (4) Multimodal interactive feedback: The intelligent interactive terminal outputs processed information in various forms such as voice, vibration, and light signals, and collects passenger feedback data, which is transmitted to the ecological service layer for continuous system optimization and service improvement.

[0032] Specifically, once the system is started, the high-sensitivity directional microphone of the audio acquisition module begins to work, collecting audio signals containing broadcast voice and background noise in the environment of the rail transit platform or carriage. Subsequently, these signals are transmitted to the audio signal processing module. In this module, the speech recognition algorithm analyzes the input signal, distinguishing the broadcast voice signal from the background noise signal. Then, for the background noise signal, adaptive noise cancellation technology comes into play, generating corresponding cancellation signals based on the real-time characteristics of the noise to reduce its interference with the broadcast voice signal. At the same time, the deep learning model enhances the broadcast voice signal, optimizing the voice features. The processed broadcast voice signal is transmitted to the power amplifier module. After being amplified to an appropriate intensity, the output module, depending on the type of hearing aid the passenger uses, transmits the signal stably to the hearing aid device via Bluetooth wireless connection or induction coil connection, ultimately allowing hearing-impaired passengers to clearly hear the broadcast voice content.

[0033] The specific innovative points of this invention include:

[0034] Dynamic adaptive acoustic processing: The system pioneered a closed-loop mechanism of "environmental perception-model optimization-real-time compensation". The system can dynamically adjust the audio processing strategy according to the train operation stage (such as acceleration and deceleration) and passenger flow density to achieve scene self-adaptation.

[0035] Privacy protection: Without leaking user data, it enables cross-regional and cross-line algorithm collaborative optimization, solving the "data silo" problem of traditional hearing aids.

[0036] Digital twin pre-research system: By digital twin modeling the acoustic environment of rail transit, it supports the virtual verification and optimization of hearing aid solutions for new lines, shortening the deployment cycle by more than 50%.

Claims

1. A hearing aid system for urban rail transit passengers, characterized in that, include: An audio acquisition module is used to acquire audio signals in the rail transit environment. The audio acquisition module uses a high-sensitivity directional microphone and prioritizes the acquisition of broadcast voice signals. An audio signal processing module, connected to the audio acquisition module, is used to process the acquired audio signal. The audio signal processing module distinguishes between broadcast voice signal and background noise signal through a speech recognition algorithm, and uses adaptive noise cancellation technology to reduce background noise interference, while enhancing the broadcast voice signal. The power amplifier module is connected to the audio signal processing module and is used to amplify the power of the processed broadcast voice signal. The output module, connected to the power amplifier module, is used to output the amplified signal to the passenger's hearing aid via Bluetooth or induction coil.

2. The urban rail transit passenger hearing aid system according to claim 1, characterized in that, The high-sensitivity directional microphone of the audio acquisition module is installed near the loudspeakers on the platform and inside the carriage, and the signal acquisition effect is optimized by adjusting the angle and position.

3. The urban rail transit passenger hearing aid system according to claim 1, characterized in that, The audio signal processing module's speech recognition algorithm and adaptive noise cancellation technology are based on a deep learning model, achieving accurate signal processing through learning and training on a large number of audio samples from the rail transit environment.

4. The urban rail transit passenger hearing aid system according to claim 1, characterized in that, The output module selectively connects to the hearing aid device via Bluetooth or induction coil, depending on the type of the passenger's hearing aid device.

Images