TWS earphones are also known as True Wireless Stereo (True Wireless Stereo) true wireless stereo. They are mainly connected to mobile phones through Bluetooth modules without wires.
The early Bluetooth technology was immature, resulting in poor sound quality, which was only suitable for business calls. After 2008, the Bluetooth A2DP protocol began popularizing, and the first batch of consumer-grade Bluetooth headsets was born. (Not True Wireless)
In 2014, the first "True Wireless" Bluetooth headset was launched. Still, the market response was not great, until after the release of Apple's Air pods in 2016, accompanied by the birth of Bluetooth 5.0 and 5.1 technology, the audio transmission loss was compressed to the minimum, the "True Wireless" Bluetooth smart headset has ushered in the outbreak.The audio quality control of TWS is also increasingly valued by the market. And audio test for TWS earphone is more and more important in the manufacture process.
In audio test for TWS earphone, different noise cancellation solutions bring users a different noise cancellation experience, MegaSig can provide customers and partners with a complete test instrument and system solutions from research and development to mass production.
Audio Test for Earphones, Headphones, TWS, Neckbands, Smart Watches, and other Audio Products. Active Noise Cancellation (ANC) and Environmental Noise Cancellation (ENC) Description and Test Technology & Methodology.
A review of Noise Suppression Technology for Real-Time Speech EnhancementIRJET Journal
This document summarizes research on noise suppression technology for real-time speech enhancement. It discusses how noise suppression has gained interest due to advances in deep learning techniques. It describes how noise suppression works by using multiple microphones to capture audio signals, which are then processed using algorithms to separate and suppress background noises while enhancing speech. Deep learning has achieved promising results for noise suppression by training models to detect human voice between different input noises. The document also reviews conventional uses of noise suppression in devices and limitations, and how using deep learning allows for more effective separation of noise from sound signals.
This document describes a project to develop an accelerometer-based contact microphone system to enable voice communication in high noise environments. The system uses accelerometers placed on the head to capture vocal vibrations, a Teensy board to perform signal processing including fast Fourier transforms and filtering, and voice recognition software to match the vocal signals to text. The goal is to filter out background noise so voices can be clearly understood. Potential applications include military, industrial, firefighting and other fields where loud noise makes communication difficult. The system was tested in various noisy conditions and showed effectiveness in distinguishing voices from background noise.
ICR is a company that provides acoustic and vibration engineering services. It was established in 1995 by experts in acoustics and has experience with national and international projects. ICR uses both theoretical knowledge and practical testing to understand problems and find solutions. It has up to 48 channels to simultaneously measure noise and vibrations in real-time. ICR provides services across various sectors including railway, wind power, and building acoustics.
ICR is a company located in Barcelona that provides acoustic and vibration engineering services. It was founded in 1995 by professionals with over 20 years of experience in vibro-acoustics. ICR offers solutions to noise and vibration problems for industries like railways, automotive, wind power, and construction. The company has PhD's, physicists, and engineers on staff that allow it to analyze vibro-acoustic problems from different perspectives. ICR provides services like noise measurements, vibration analysis, environmental impact studies, and software development to solve clients' noise and vibration issues.
Sound Measurement" by Onosokki is a cutting-edge and comprehensive collection of precision instruments and solutions designed to unravel the complexities of sound analysis. This product, developed by the prestigious Onosokki firm, a world authority in measuring and testing technology, raises the bar for precise and trustworthy sound measurement.
Review Paper on Noise Reduction Using Different TechniquesIRJET Journal
This document reviews different techniques for noise reduction in hearing aids. It discusses how digital hearing aids use algorithms like fast Fourier transforms and adaptive filters to separate speech from noise and improve speech comprehension in noisy environments. The document also evaluates different noise reduction algorithms and filter bank designs that have been proposed in previous research to enhance the noise reduction capabilities of hearing aids. The goal of developing improved noise reduction for hearing aids is to help hearing-impaired individuals better understand speech in various real-world settings with background noise.
Audio Test for Earphones, Headphones, TWS, Neckbands, Smart Watches, and other Audio Products. Active Noise Cancellation (ANC) and Environmental Noise Cancellation (ENC) Description and Test Technology & Methodology.
A review of Noise Suppression Technology for Real-Time Speech EnhancementIRJET Journal
This document summarizes research on noise suppression technology for real-time speech enhancement. It discusses how noise suppression has gained interest due to advances in deep learning techniques. It describes how noise suppression works by using multiple microphones to capture audio signals, which are then processed using algorithms to separate and suppress background noises while enhancing speech. Deep learning has achieved promising results for noise suppression by training models to detect human voice between different input noises. The document also reviews conventional uses of noise suppression in devices and limitations, and how using deep learning allows for more effective separation of noise from sound signals.
This document describes a project to develop an accelerometer-based contact microphone system to enable voice communication in high noise environments. The system uses accelerometers placed on the head to capture vocal vibrations, a Teensy board to perform signal processing including fast Fourier transforms and filtering, and voice recognition software to match the vocal signals to text. The goal is to filter out background noise so voices can be clearly understood. Potential applications include military, industrial, firefighting and other fields where loud noise makes communication difficult. The system was tested in various noisy conditions and showed effectiveness in distinguishing voices from background noise.
ICR is a company that provides acoustic and vibration engineering services. It was established in 1995 by experts in acoustics and has experience with national and international projects. ICR uses both theoretical knowledge and practical testing to understand problems and find solutions. It has up to 48 channels to simultaneously measure noise and vibrations in real-time. ICR provides services across various sectors including railway, wind power, and building acoustics.
ICR is a company located in Barcelona that provides acoustic and vibration engineering services. It was founded in 1995 by professionals with over 20 years of experience in vibro-acoustics. ICR offers solutions to noise and vibration problems for industries like railways, automotive, wind power, and construction. The company has PhD's, physicists, and engineers on staff that allow it to analyze vibro-acoustic problems from different perspectives. ICR provides services like noise measurements, vibration analysis, environmental impact studies, and software development to solve clients' noise and vibration issues.
Sound Measurement" by Onosokki is a cutting-edge and comprehensive collection of precision instruments and solutions designed to unravel the complexities of sound analysis. This product, developed by the prestigious Onosokki firm, a world authority in measuring and testing technology, raises the bar for precise and trustworthy sound measurement.
Review Paper on Noise Reduction Using Different TechniquesIRJET Journal
This document reviews different techniques for noise reduction in hearing aids. It discusses how digital hearing aids use algorithms like fast Fourier transforms and adaptive filters to separate speech from noise and improve speech comprehension in noisy environments. The document also evaluates different noise reduction algorithms and filter bank designs that have been proposed in previous research to enhance the noise reduction capabilities of hearing aids. The goal of developing improved noise reduction for hearing aids is to help hearing-impaired individuals better understand speech in various real-world settings with background noise.
Performance enhancement of dct based speaker recognition using wavelet de noi...eSAT Journals
Abstract Presence of noise in the speech signal is one of the major problems in Speaker Recognition. The speaker recognition performance gradually degrades as the intensity of noise increases. The system gives high accuracy when the speech signal is noise free, but in real life scenario getting a noise free speech signal is challenging. Hence, elimination of the noise from speech signal is an important aspect in speaker recognition process. This work uses wavelet based denoising of the recorded speech signal in order to enhance the performance of speaker recognition. In this paper, wavelet based denoising technique has been applied to the DCT based speaker recognition system which was proposed in our previous work. Additive white Gaussian noise has been added to the speech signal and performance analysis of the system has been done using different SNR value. Keywords: Wavelet denoising, AWGN, Speaker Recognition, Thresholding, DCT, Feature Extraction.
Development of Algorithm for Voice Operated Switch for Digital Audio Control ...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
silent sound technology final report(17321A0432) (1).pdfssuser476810
The document is a seminar report on silent sound technology submitted by Divya Alugubelli. It discusses the need for silent sound technology, which allows communication without noise pollution by detecting lip movements and converting them to sound signals. The report covers two main methods - electromyography and image processing. Electromyography monitors tiny muscle movements during speech and converts them to electrical pulses that can be translated to sound. Image processing techniques detect lip movements through a webcam and analyze the images. The technology has applications in helping those who have lost their voice and allows silent calling without disturbing others.
Smart Sound Measurement and Control System for Smart CityIRJET Journal
This document summarizes a research paper that proposes a smart sound measurement and control system for smart cities using Internet of Things technology. The system aims to address issues with existing noise measurement devices, such as only detecting noise in limited nearby areas. The proposed system would use multiple inexpensive sound detection devices connected via WiFi that send sensor data to the cloud to be viewed on mobile devices. This would allow for averaging readings across devices and monitoring noise levels in larger spaces. The system is intended to help authorities better enforce noise regulations and view historical noise data to address noise pollution issues near hospitals, schools and other areas that require quiet environments.
Effect of Speech enhancement using spectral subtraction on various noisy envi...IRJET Journal
This document discusses speech enhancement techniques using spectral subtraction. It begins with an abstract discussing analysis modification synthesis (AMS) and various speech enhancement features. It then discusses conventional spectral subtraction which estimates noise spectra and subtracts it from noisy speech spectra. Experimental evaluation uses the NOIZEUS speech corpus with noise at various signal-to-noise ratios. Objective measures like PESQ, Csig and Covl scores show the proposed method effectively reduces noise. Spectrogram analysis demonstrates noise reduction at lower frequencies. The document concludes spectral subtraction methods can improve speech quality in noisy environments.
IRJET- Survey on Efficient Signal Processing Techniques for Speech EnhancementIRJET Journal
This document provides a survey of various speech enhancement techniques. It discusses five papers that propose different speech enhancement algorithms: 1) Discrete Tchebichef Transform and Discrete Krawtchouk Transform for removing noise using minimum mean square error. 2) Empirical mode decomposition and adaptive centre weighted average filtering that is effective for removing noise components. 3) Adaptive Wiener filtering that adapts the filter transfer function based on speech signal statistics. 4) Compressive sensing based speech enhancement that handles non-sparse noise. 5) Wavelet packet transform and non-negative matrix factorization to emphasize the speech components in each sub-band. The document also discusses speech enhancement using deep neural networks, empirical mode decomposition with Hurst exponent
Research work ppt on speech intelligibility quality in telugu speech patterns...chinavs
This document presents a paper on improving the intelligibility of Telugu speech patterns using a wavelet-based hybrid threshold transform method. It discusses how noise can reduce speech intelligibility in industrial areas and for applications like voice recognition. It proposes a new algorithm using multiband spectral subtraction and different transform techniques like Haar and Daubechies transforms to remove noise and improve speech quality. The paper compares this approach to existing methods like spectral subtraction and Wiener filtering through various objective measures.
Unwelcomed workplace noise disrupts concentration, decreases productivity and increases stress amongst your associates according to a recent University of California study. And these are challenges that are being over-looked in even the most modern of working environments.
This guide illustrates the key acoustic challenges and the measures needed to minimise their effect on your smarter working environment.
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...IRJET Journal
This document provides an overview of wave ultrasonic testing and how varying operational parameters can improve its characteristics. It discusses how guided wave testing using low frequencies below 100 kHz can be used to inspect pipes over long distances for corrosion detection. Commercial systems have been developed that use arrays of piezoelectric transducers to generate and control axially symmetric modes to identify non-symmetric features indicating defects. Varying the test frequency affects sensitivity, resolution, and range, with lower frequencies providing longer ranges but reduced resolution.
Explore precision in sound measurement with Class 1 and Class 2 Sound Level Meter. Achieve accurate results effortlessly, whether for industrial settings or environmental monitoring. Elevate your sound analysis with cutting-edge technology.
complete seminar report on the topic silent sound technology given by raj niranjan in MCA department of BMS Institute of Technology and Management , avalahalli,bangalore ,karnataka
The Ono Sokki dB Meter will take noise monitoring and evaluation to a new level. This tool equips anyone concerned about the effects of noise, whether they are sound engineers, environmental analysts, safety officers, or other professionals, to make informed judgments, put up practical solutions, and help create a society that is quieter and more sustainable. Accept the Ono Sokki dB Meter as the noise measurement tool of the future.
ACTIVE NOISE CANCELLATION IN A LABORATORY DUCT USING FUZZY LOGIC AND NEURAL ...Rishikesh .
The main goal of this paper is to present a simulation scheme to simulate an adaptive filter using LMS (Least mean square) adaptive algorithm for noise cancellation. The main objective of the noise cancellation is to estimate the noise signal and to subtract it from original input signal plus noise signal and hence to obtain the noise free signal. There is an alternative method called adaptive noise cancellation for estimating a speech signal corrupted by an additive noise or interference. This method uses a primary input signal that contains the speech signal and a reference input containing noise. The reference input is adaptively filtered and subtracted from the primary input signal to obtain the estimated signal. In this method the desired signal corrupted by an additive noise can be recovered by an adaptive noise canceller using LMS (least mean square) algorithm. This adaptive noise canceller is useful to improve the S/N ratio. Here we estimate the adaptive filter using Labview /MATLAB/SIMULINK environment . For achieving the goal we also use modern algorithms like ANFIS, FIS and Neural Network and compare the PSD of all the algorithms.
Distance Measurement Using Ultrasonic Sensor and NodemcuIRJET Journal
This document describes a distance measurement system using an ultrasonic sensor and NodeMCU microcontroller. The system is designed to remotely monitor and measure distances of obstacles for surveillance purposes. It works by sending ultrasonic pulses and measuring the echo return time to calculate distance. The NodeMCU transmits distance data from the ultrasonic sensor to a smartphone app via WiFi in real-time. The system allows remote monitoring of areas with obstacles detected and distance information sent automatically to a mobile device.
Sorynory is launching a new Bluetooth hearing aid called Sorynory Hearing Aid. It has an ergonomic design and comes in stylish options. It has over 45 hours of battery life, 32 channels, and connects to devices via Bluetooth. The hearing aid analyzes the user's environment to provide accurate fittings and reduces noise and shifts frequencies for clearer sound. It is controlled by a smartphone app that provides fitting and remote analysis services to enhance speech recognition.
IRJET- Hearing Loss Detection through Audiogram in Mobile DevicesIRJET Journal
This document describes a mobile application called HearAssist that detects hearing loss through audiograms on mobile devices. The app aims to create accurate audiogram reports for users by playing tones of varying frequencies and intensities and having users respond if they can hear each one. The reports are stored in a database to analyze trends in hearing capabilities across age groups. The app aims to make audiogram testing more accessible and convenient compared to traditional methods by generating reports on a mobile device from the comfort of home.
Prince Gupta presented on silent sound technology, which allows communication without vocalizing. It uses electromyography to monitor muscle movements when speaking and converts them into electrical pulses and speech. Image processing of lip movements is another method. Advantages include silent phone calls and sharing confidential information discreetly. Applications include military communication and use by astronauts and those who cannot speak. Future improvements could incorporate the sensors directly into phones rather than using separate devices.
This document provides a report on the capstone project to design a microstrip antenna for wireless applications by integrating embedded systems and IoT. It begins with an acknowledgment section thanking the project supervisor. The next sections include an introduction on antenna design, the design parameters considered, an overview of how the project works, details on the CST simulation software used, the antenna design process in CST, a literature review, and conclusions. Key aspects of the project involve designing a microstrip antenna using different feeding techniques, integrating it with an embedded system for data transmission via IoT, and using CST software to simulate and optimize the antenna performance.
IOT BASED VIBRATION VEST FOR DEAF PEOPLEIRJET Journal
This document describes a proposed IOT-based vibration vest to help deaf people sense sounds. The vest uses a microphone to capture sounds, an Arduino microprocessor to process the sounds using Fast Fourier Transform (FFT) algorithm, and vibration motors to convert the processed sounds into vibrations. The microprocessor analyzes the sound frequencies and amplitudes and sends corresponding signals to the vibration motors to produce unique vibration patterns. This allows deaf people to experience and learn about sounds through felt vibrations rather than heard sounds. The proposed system aims to provide a low-cost and effective way for deaf people to sense sounds in their environment.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Performance enhancement of dct based speaker recognition using wavelet de noi...eSAT Journals
Abstract Presence of noise in the speech signal is one of the major problems in Speaker Recognition. The speaker recognition performance gradually degrades as the intensity of noise increases. The system gives high accuracy when the speech signal is noise free, but in real life scenario getting a noise free speech signal is challenging. Hence, elimination of the noise from speech signal is an important aspect in speaker recognition process. This work uses wavelet based denoising of the recorded speech signal in order to enhance the performance of speaker recognition. In this paper, wavelet based denoising technique has been applied to the DCT based speaker recognition system which was proposed in our previous work. Additive white Gaussian noise has been added to the speech signal and performance analysis of the system has been done using different SNR value. Keywords: Wavelet denoising, AWGN, Speaker Recognition, Thresholding, DCT, Feature Extraction.
Development of Algorithm for Voice Operated Switch for Digital Audio Control ...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
silent sound technology final report(17321A0432) (1).pdfssuser476810
The document is a seminar report on silent sound technology submitted by Divya Alugubelli. It discusses the need for silent sound technology, which allows communication without noise pollution by detecting lip movements and converting them to sound signals. The report covers two main methods - electromyography and image processing. Electromyography monitors tiny muscle movements during speech and converts them to electrical pulses that can be translated to sound. Image processing techniques detect lip movements through a webcam and analyze the images. The technology has applications in helping those who have lost their voice and allows silent calling without disturbing others.
Smart Sound Measurement and Control System for Smart CityIRJET Journal
This document summarizes a research paper that proposes a smart sound measurement and control system for smart cities using Internet of Things technology. The system aims to address issues with existing noise measurement devices, such as only detecting noise in limited nearby areas. The proposed system would use multiple inexpensive sound detection devices connected via WiFi that send sensor data to the cloud to be viewed on mobile devices. This would allow for averaging readings across devices and monitoring noise levels in larger spaces. The system is intended to help authorities better enforce noise regulations and view historical noise data to address noise pollution issues near hospitals, schools and other areas that require quiet environments.
Effect of Speech enhancement using spectral subtraction on various noisy envi...IRJET Journal
This document discusses speech enhancement techniques using spectral subtraction. It begins with an abstract discussing analysis modification synthesis (AMS) and various speech enhancement features. It then discusses conventional spectral subtraction which estimates noise spectra and subtracts it from noisy speech spectra. Experimental evaluation uses the NOIZEUS speech corpus with noise at various signal-to-noise ratios. Objective measures like PESQ, Csig and Covl scores show the proposed method effectively reduces noise. Spectrogram analysis demonstrates noise reduction at lower frequencies. The document concludes spectral subtraction methods can improve speech quality in noisy environments.
IRJET- Survey on Efficient Signal Processing Techniques for Speech EnhancementIRJET Journal
This document provides a survey of various speech enhancement techniques. It discusses five papers that propose different speech enhancement algorithms: 1) Discrete Tchebichef Transform and Discrete Krawtchouk Transform for removing noise using minimum mean square error. 2) Empirical mode decomposition and adaptive centre weighted average filtering that is effective for removing noise components. 3) Adaptive Wiener filtering that adapts the filter transfer function based on speech signal statistics. 4) Compressive sensing based speech enhancement that handles non-sparse noise. 5) Wavelet packet transform and non-negative matrix factorization to emphasize the speech components in each sub-band. The document also discusses speech enhancement using deep neural networks, empirical mode decomposition with Hurst exponent
Research work ppt on speech intelligibility quality in telugu speech patterns...chinavs
This document presents a paper on improving the intelligibility of Telugu speech patterns using a wavelet-based hybrid threshold transform method. It discusses how noise can reduce speech intelligibility in industrial areas and for applications like voice recognition. It proposes a new algorithm using multiband spectral subtraction and different transform techniques like Haar and Daubechies transforms to remove noise and improve speech quality. The paper compares this approach to existing methods like spectral subtraction and Wiener filtering through various objective measures.
Unwelcomed workplace noise disrupts concentration, decreases productivity and increases stress amongst your associates according to a recent University of California study. And these are challenges that are being over-looked in even the most modern of working environments.
This guide illustrates the key acoustic challenges and the measures needed to minimise their effect on your smarter working environment.
IRJET- Wave Ultrasonic Testing and how to Improve its Characteristics by Vary...IRJET Journal
This document provides an overview of wave ultrasonic testing and how varying operational parameters can improve its characteristics. It discusses how guided wave testing using low frequencies below 100 kHz can be used to inspect pipes over long distances for corrosion detection. Commercial systems have been developed that use arrays of piezoelectric transducers to generate and control axially symmetric modes to identify non-symmetric features indicating defects. Varying the test frequency affects sensitivity, resolution, and range, with lower frequencies providing longer ranges but reduced resolution.
Explore precision in sound measurement with Class 1 and Class 2 Sound Level Meter. Achieve accurate results effortlessly, whether for industrial settings or environmental monitoring. Elevate your sound analysis with cutting-edge technology.
complete seminar report on the topic silent sound technology given by raj niranjan in MCA department of BMS Institute of Technology and Management , avalahalli,bangalore ,karnataka
The Ono Sokki dB Meter will take noise monitoring and evaluation to a new level. This tool equips anyone concerned about the effects of noise, whether they are sound engineers, environmental analysts, safety officers, or other professionals, to make informed judgments, put up practical solutions, and help create a society that is quieter and more sustainable. Accept the Ono Sokki dB Meter as the noise measurement tool of the future.
ACTIVE NOISE CANCELLATION IN A LABORATORY DUCT USING FUZZY LOGIC AND NEURAL ...Rishikesh .
The main goal of this paper is to present a simulation scheme to simulate an adaptive filter using LMS (Least mean square) adaptive algorithm for noise cancellation. The main objective of the noise cancellation is to estimate the noise signal and to subtract it from original input signal plus noise signal and hence to obtain the noise free signal. There is an alternative method called adaptive noise cancellation for estimating a speech signal corrupted by an additive noise or interference. This method uses a primary input signal that contains the speech signal and a reference input containing noise. The reference input is adaptively filtered and subtracted from the primary input signal to obtain the estimated signal. In this method the desired signal corrupted by an additive noise can be recovered by an adaptive noise canceller using LMS (least mean square) algorithm. This adaptive noise canceller is useful to improve the S/N ratio. Here we estimate the adaptive filter using Labview /MATLAB/SIMULINK environment . For achieving the goal we also use modern algorithms like ANFIS, FIS and Neural Network and compare the PSD of all the algorithms.
Distance Measurement Using Ultrasonic Sensor and NodemcuIRJET Journal
This document describes a distance measurement system using an ultrasonic sensor and NodeMCU microcontroller. The system is designed to remotely monitor and measure distances of obstacles for surveillance purposes. It works by sending ultrasonic pulses and measuring the echo return time to calculate distance. The NodeMCU transmits distance data from the ultrasonic sensor to a smartphone app via WiFi in real-time. The system allows remote monitoring of areas with obstacles detected and distance information sent automatically to a mobile device.
Sorynory is launching a new Bluetooth hearing aid called Sorynory Hearing Aid. It has an ergonomic design and comes in stylish options. It has over 45 hours of battery life, 32 channels, and connects to devices via Bluetooth. The hearing aid analyzes the user's environment to provide accurate fittings and reduces noise and shifts frequencies for clearer sound. It is controlled by a smartphone app that provides fitting and remote analysis services to enhance speech recognition.
IRJET- Hearing Loss Detection through Audiogram in Mobile DevicesIRJET Journal
This document describes a mobile application called HearAssist that detects hearing loss through audiograms on mobile devices. The app aims to create accurate audiogram reports for users by playing tones of varying frequencies and intensities and having users respond if they can hear each one. The reports are stored in a database to analyze trends in hearing capabilities across age groups. The app aims to make audiogram testing more accessible and convenient compared to traditional methods by generating reports on a mobile device from the comfort of home.
Prince Gupta presented on silent sound technology, which allows communication without vocalizing. It uses electromyography to monitor muscle movements when speaking and converts them into electrical pulses and speech. Image processing of lip movements is another method. Advantages include silent phone calls and sharing confidential information discreetly. Applications include military communication and use by astronauts and those who cannot speak. Future improvements could incorporate the sensors directly into phones rather than using separate devices.
This document provides a report on the capstone project to design a microstrip antenna for wireless applications by integrating embedded systems and IoT. It begins with an acknowledgment section thanking the project supervisor. The next sections include an introduction on antenna design, the design parameters considered, an overview of how the project works, details on the CST simulation software used, the antenna design process in CST, a literature review, and conclusions. Key aspects of the project involve designing a microstrip antenna using different feeding techniques, integrating it with an embedded system for data transmission via IoT, and using CST software to simulate and optimize the antenna performance.
IOT BASED VIBRATION VEST FOR DEAF PEOPLEIRJET Journal
This document describes a proposed IOT-based vibration vest to help deaf people sense sounds. The vest uses a microphone to capture sounds, an Arduino microprocessor to process the sounds using Fast Fourier Transform (FFT) algorithm, and vibration motors to convert the processed sounds into vibrations. The microprocessor analyzes the sound frequencies and amplitudes and sends corresponding signals to the vibration motors to produce unique vibration patterns. This allows deaf people to experience and learn about sounds through felt vibrations rather than heard sounds. The proposed system aims to provide a low-cost and effective way for deaf people to sense sounds in their environment.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
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Consumer Electronics Testing
Related
Audio Test for TWS Earphone
MegaSig Measurement & Control Technology Co. Ltd.
www.megasig.com
2. Equips engineers to create better products
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2nd
Update Date Responsible Description
2022.11.10 Jiang Weiyuan First Draft
Table of Contents
1、The development history of TWS headphones...........................................................................................3rd
2、Introduction to the concept of ENC/ANC.................................................................................................. 3rd
2.1、ENC Concept................................................................................................................................... 3rd
2.2、ANC concept.................................................................................................................................... 4th
3、ENC and ANC test solutions.......................................................................................................................5th
3.1、ENC test solution............................................................................................................................. 5th
3.2、ANC test solution........................................................................................................................... 11th
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3rd
1. The development history of TWS earphones
TWS earphones are also known as True Wireless Stereo (True Wireless Stereo) true wireless
stereo. They are mainly connected to mobile phones through Bluetooth modules without wires.
The early Bluetooth technology was immature, resulting in poor sound quality, which was only
suitable for business calls. After 2008, the Bluetooth A2DP protocol began popularizing, and the first
batch of consumer-grade Bluetooth headsets was born. (Not True Wireless)
In 2014, the first "True Wireless" Bluetooth headset was launched. Still, the market response was
not great, until after the release of Apple's Air pods in 2016, accompanied by the birth of Bluetooth
5.0 and 5.1 technology, the audio transmission loss was compressed to the minimum, the "True
Wireless" Bluetooth smart headset has ushered in the outbreak.The audio quality control of TWS is
also increasingly valued by the market. And audio test for TWS earphone is more and more
important in the manufacture process.
2.2 Introduction to the concept of ENC/ANC
2.1 ENC Concept
Active noise cancellation and environment noise cancellation are different noise cancellation
technologies. Active noise cancellation is to offset ambient environment noise to the greatest extent,
allowing people using headphones to enjoy a quiet environment, while environment noise
cancellation is an application in the other direction, it allows people using noise-canceling
headphones to make a call on the side of a noisy road, on a speeding motorcycle, in a moving car
with music on, or in a car with windows open. The person on the other side of the phone can hear
your speech clearly, and the noise basically does not pass. Simply it means, active noise
cancellation means that people who use headphones feel better, and environment noise
cancellation means that people on the other end of the phone feel better. In audio test for TWS
earphone, ENC function is also very important to test.
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2.2 ANC concept
With the development of TWS technology, another equally popular technology is ANC (Active Noise
Cancellation), which is active noise cancellation, a kind of noise reduction technology applied in the
headphones for noise reduction.
The ANC noise reduction technology analyzes the sound waves of the noise, and then
superimposes and neutralizes them by sending reverse sound waves, so as to achieve the effect of
eliminating noise. The advantage is that the control effect of low-frequency noise is remarkable, and
it can effectively isolate low-frequency noise and reduce the impact of noise on people's health. In
general, the effective frequency of ANC active noise cancellation is between 50Hz and 2kHz. For
noise exceeding 2KHz, noise-cancellation headphones can reduce it by using passive methods
through the structural design and material selection of the headphones. In audio test for TWS
earphone, ANC performance is also very important to test.
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3 ENC and ANC test solutions
Different noise cancellation solutions bring users a different noise cancellation experience, MegaSig
can provide customers and partners with a complete test instrument and system solutions from
research and development to mass production.
3.1 ENC test solution
First let's take a look at ENC's test solutions in audio test for TWS earphone
There are 3 main technologies for noise reduction in calls:
1,Beam-forming directional enhancement technology
2,Adaptive filtering technology
3,Uplink bone conduction technology
These three technologies are not new in audio test. Our mobile phones have two microphones (one
is next to the charging port and the other is next to the camera), which have been silently helping us
make calls and noise reduction for many years (so, sometimes we are accustomed to turning off the
earphones and using the mobile phone directly when making a phone call with earphones for fear of
being unclear. This is the main reason).
The essence of uplink bone conduction technology is to transmit the call content by collecting the
vibration signal of face or vocal cord. The noise conduction medium is air, and the vibration of your
face or vocal cords are directly collected by the acceleration sensor, which can isolate the
environmental noise. This technology is widely used in the military, making a phone call in a tank or
in a helicopter.
3.1.1 Environmental Noise Cancellation effect test in the Research and
Development stage
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a) Environmental Noise Cancellation of Beam-forming algorithm in research and
development stage
The following figure shows the effect of TWS headphones with Beam-forming in our office.
The system architecture is in the figure below. We use the turntable TT625 to measure the HFP
transmission energy of each angle of the earphone. If we use the frequency sweep signal, it can be
considered that the adaptive filter has not converged yet, i.e., the received signal can be considered
to be enhanced by beam-forming only.
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b) Adaptive filtering algorithm in R&D stage
R&D testing not only needs to quantify the beam-forming effect, but also needs to carry out the
convergence effect of the adaptive filter, and even test the convergence time. Both of them are
supported by AudioExpert platform.
c) Bone conduction technology in the R&D stage
In audio test for TWS earphone, bone conduction can be divided into uplink/downlink bone
conduction call technology, the former is to allow the other party to hear clearly, and the latter is to
allow yourself to hear clearly. We will focus on the uplink bone conduction technology.
In the process of talking, the sound of our own speech is the useful signal we really want to
transmit, but in addition, there are various noises generated by machinery and equipment, wind
noise, surrounding people, etc., which can be called Noise signals.
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The essence of the uplink bone conduction technology is to collect the vibration signal of the cheek
by inserting an acceleration sensor chip into the earphone and transmit the effective signal as the
content of the call. The conduction (air conduction) of the ambient noise depends on the microphone,
so it will not be collected by the acceleration sensor, which can achieve the effect of air conduction
noise filtering.
When we speak, in addition to the vibration of the face, the vibration of the bridge of the nose is also
relatively strong, so this technology is not only used in the field of headsets, but also in VR or AR
smart wearable devices to improve the effect of calls.
From the test of the uplink bone conduction call technology, it can be divided into three parts: the
incoming IQC chip test, the semi-finished bone voiceprint test and the finished bone voiceprint test.
The following three tests are supported and compatible with our MegaSig system.
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3.1.2 Test of call noise reduction effect in mass production
Over the past two years, MegaSig has supported batches of headsets with ENC function and mass
production testing of TWS earphones with ENC function. Now we will introduce the accumulated
experience to you.
There are 3 main testing methods for mass production:
1, Signal-to-noise ratio test
2, Loop test
3, Switch test
There are advantages and disadvantages to these three methods in audio test for TWS earphone,
and the system of MegaSig supports them seamlessly. The analysis and introduction are below.
1) Signal-to-Noise Ratio test
This method does not require the support of the chip manufacturer's instructions, and basically, any
instrument can support it, and the measurement environment is similar to the real-time environment,
and the noise reduction data tested is close to the real effect. However, because the algorithm is
always on, it is easy to be disturbed by the environment, and the test data is not very stable.
Sometimes it needs to be retested to pass, and it takes some time to wait for convergence, so the
test efficiency and yield are relatively low.
2) Loop test
This method requires the support of chip manufacturers or solution providers and have to control the
DUT. Moreover, in the form of TWS, it does not support too many thimble points, so SPP or BLE
protocol is generally used. However, since this test method strips the influence of the algorithm, it is
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possible to measure the quality and assembly errors of the dual microphones. The consistency is
very high, there is no convergence time, and the test efficiency is also high. High-end brands also
pay attention to ENC quality, basically will tend to use this method. At present, MegaSig’s system
can support the DUT control of the general Bluetooth chips on the market.
3) Switch test
In this method, the penetration effect of noise energy is tested through the switch of the DUT.
Since this test has only one angle, the noise suppression capability of beam-forming is basically
ignored, the DUT command is also required, and the convergence time is required, so this
method is least recommended for mass production. However, it is recommended to use it in the
research and development stage to test the effect of the adaptive filter, and some manufacturers
choose this method in the early mass production test of single-mic noise reduction.
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3.2 ANC test solution
In audio test for TWS earphone, the noise reduction effect of ANC noise-canceling headphones is
determined by two aspects, one is the design of the filter chain of the product, and the other is a
series of noise reduction gain values of the product. In the R&D stage, the filter chain design has
been finalized and will not be changed in the mass production stage. However, due to the difference
in the quality of incoming materials for the microphone unit and the speaker unit, as well as the
cavity difference generated during the assembly process, to make up for these tolerance and
achieve the target noise reduction effect and balance the noise reduction effect, during mass
production, the noise reduction gain value needs to be fine-tuned and modified, and the noise
reduction effect can be tested online. The traditional method is to manually adjust the gain, manually
verify it until it meets the noise reduction effect, and then manually burn it.
AudioExpert's ANC option supports all mainstream noise reduction solutions on the market, as well
as automated testing and burning systems. MegaSig cooperates with first-class ODM
manufacturers and solution providers and has successfully pushed this system to R&D and Mass
production, creating value for customers stably and efficiently.
The system also supports the measurement of key electro-acoustic parameters that are concerned
in the production process of headphones, microphones, and other components when the ANC
function is turned off. It is a one-stop test system.
The software parameter configuration of the system is simple and fast, the testing process is fast
and accurate, the production efficiency is maximized, the product quality is guaranteed, and the
company wins the time and the trust of the customers, and finally obtains a larger order and
achieves a win-win situation.
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ANC noise reduction automation test Universal architecture