Sound Output Research Articles

Morten Qvenild – The HyPer(sonal) Piano Project

Towards a (per)sonal topography of grand piano and electronics How can I develop a grand piano with live electronics through iterated development loops in the cognitive technological environment of instrument, music, performance and my poetics? The instrument I am developing, a grand piano with electronic augmentations, is adapted to cater my poetics. This adaptation of the instrument will change the way I compose. The change of composition will change the music. The change of music will change my performances. The change in performative needs will change the instrument, because it needs to do different things. This change in the instrument will show me other poetics and change my ideas. The change of ideas demands another music and another instrument, because the instrument should cater to my poetics. And so it goes… These are the development loops I am talking about. I have made an augmented grand piano using various music technologies. I call the instrument the HyPer(sonal) Piano, a name derived from the suspected interagency between the extended instrument (HyPer), the personal (my poetics) and the sonal result (music and sound). I use old analogue guitar pedals and my own computer programming side by side, processing the original piano sound. I also take out control signals from the piano keys to drive different sound processes. The sound output of the instrument is deciding colors, patterns and density on a 1x3 meter LED light carpet attached to the grand piano. I sing, yet the sound of my voice is heavily processed, a processing decided by what I am playing on the keys. All sound sources and control signal sources are interconnected, allowing for complex and sometimes incomprehensible situations in the instrument´s mechanisms. Credits: First supervisor: Henrik Hellstenius Second Supervisors: Øyvind Brandtsegg and Eivind Buene Cover photo by Jørn Stenersen, www.anamorphiclofi.com All other photo, audio and video recording/editing by Morten Qvenild, unless stated.

Identification of Key Performance Metrics for Different Ultrasonic Surgical Devices

Abstract Ultrasonic surgical devices utilize high-frequency sound waves to perform surgical tasks, including cutting, fragmenting, emulsifying, and sealing tissues. Their multifunctional capabilities have facilitated their broad application across various surgical disciplines, such as general surgery, neurosurgery, and orthopedic surgery. While the current international standard, IEC 61847:1998 “Ultrasonics - Surgical Systems - Measurement and Declaration of the Basic Output Characteristics”, outlines a set of fundamental output characteristics for these devices, the diverse applications and performance requirements of each device necessitate the identification of key performance metrics. In this study, we delve into the applicability of these basic output characteristics for different ultrasonic surgical devices. Through comprehensive experimental evaluations on biological tissues, we assessed the influence of specific parameters, namely drive frequency, excursion amplitude, power output, duty cycle, and primary sound output area, on the cutting efficiency and coagulation results of three distinct ultrasonic surgical devices. Our results highlight the paramount parameters that govern the primary functions of these devices. This research offers invaluable insights for device manufacturers and evaluators, guiding them in prioritizing and emphasizing crucial parameters during the design, manufacturing, and evaluation phases of ultrasonic surgical devices.

Acapella-based music generation with sequential models utilizing discrete cosine transform

Making musical instruments that accompany vocals in a song depends on the mood quality and the music composer’s creativity. The model created by other researchers has restrictions that include being limited to musical instrument digital interface files and relying on recurrent neural networks (RNN) or Transformers for the recursive generation of musical notes. This research offers the world’s first model capable of automatically generating musical instruments accompanying human vocal sounds. The model we created is divided into three types of sound input: short input, combed input, and frequency sound based on the discrete cosine transform (DCT). By combining the sequential models such as Autoencoder and gated recurrent unit (GRU) models, we will evaluate the performance of the resulting model in terms of loss and creativity. The best model has a performance evaluation that resulted in an average loss of 0.02993620155. The hearing test results from the sound output produced in the frequency range 0-1,600 Hertz can be heard clearly, and the tones are quite harmonious. The model has the potential to be further developed in future research in the field of sound processing.

Implementation of Finite State Automata Method in Text to Speech Conversion System

Sound processing uses a variety of methods. One of them is converting writing into sound or commonly known as Text To Speech.Text To Speech is a tool for converting writing input into sound by changing the phoneme of writing.Text To Speech Text To Speech consists of two sub-systems namely word to phoneme converters and phoneme to speech converter. The phoneme itself consists of word fragments that have different speech from one another with each other. To perform the phoneme separation process, the Finite State Automata method. Finite State Automata can recognise the simplest language and is an abstract machine whose input and output are discrete. The input system that is processed by the system only consists of two words. If there are more than two word inputs, the programme will not be able to perform word separation properly. After the word separation is done, then the system performs phoneme to speech converter.The resulting speech is processed by the Indo_TTS database which was database developed using the diphone prosody method concatenation prosody methodThe word that has been separated will be stored into the MySQL database as a result of words that have been tested by the system. Later this system will be intended for general public, students and people with speech impairment. The percentage of successful syllable separation and homograph sound output is 98.7% in the programme's success rate.

Development of Sign Language Interpreter Glove for Speech-Impaired Deaf Individuals with Levenshtein Algorithm as an Autotext Correction System.

Assistive technology is technology developed in the form of aids, adaptive tools, and rehabilitation for individuals with disabilities to compensate for their lacking abilities. With assistive technology available to people with special needs, it can help them enhance their independent living skills and reduce their dependence on others, including in communication activities. This research aims to assess the feasibility of developing assistive technology for the speech-impaired, specifically a glove that can translate the SIBI letter sequence into words displayed on a 6 x 12 LCD screen and also produce sound output from the sign language hand movements of speech-impaired individuals when using the glove. The research method used in this study is Research and Development (R&D). The calibration test phase indicated that the prototype was in good condition, as evidenced by an accuracy rate above 90% for voltage at 0◦ and 90◦ angles produced by each finger. Consequently, the next calibration phase, which involves translating sensor readings into SIBI letters through digital data values, can be carried out by taking the ADC values of each finger. Subsequently, the glove was tested to read 7 out of 20 alphabets and achieved a success rate of ≥ 90% for 5 alphabets. The lowest success rate was 70% for the letter E. The average success rate for the 7 alphabet experiments was 91.4%. In the field test phase, the glove was tested on a deaf-mute student to form several words, and the output text displayed on the LCD and audio output matched the readings corrected by the auto-text correction system.

Digital Measuring Instruments for Height and Weight with Microcontroller-Based Sound Output

Height and weight measuring devices simultaneously provide ideal weight information that will be handy for users. This study aims to provide an instrument that can be used as a measuring instrument for height and weight and whether or not a person's body is ideal. Therefore, in research, measuring instruments that can simultaneously measure height and weight and provide ideal information or not measured weight. This measuring instrument uses Arduino Uno as its brain, ultrasonic sensors to measure height, and strain gauge/load cell sensors to measure weight. Arduino processes data from both sensors to get the ideal body weight (BBI). The height, weight, and ideal body criteria values will be displayed on the LCD. Furthermore, the speaker will issue sound information regarding the condition of body weight, namely ideal, fat, or thin. Based on the testing and data analysis results, the average error percentage value in height measurement is 0.45%, and in weight measurement is 1.65%. At the same time, the success rate of the appearance of voice information is 99%.

Automated Digital Wind Instrument using Arduino UNO Microcontroller

Recently, Blackstar Amplification Ltd. has introduced a Compact Carry-On Digital Wind Instrument (CDWI), mirroring the design of traditional recorder instruments in their size and shape. This CDWI can be played as a traditional wind instrument by blowing into the mouthpiece and simultaneously manipulating finger holes, enabling the production of desired musical notes. The main aim of this research work is the development of a prototype model to automate the CDWI, by utilizing the Arduino UNO microcontroller board and introducing the Automated Digital Wind Instrument (ADWI). The CDWI has a mouthpiece, nine finger holes, and one thumb hole, and the blowing mechanism can be automated by using a 12 Volts DC air blower and a servo valve. The author ingeniously develops a new servo valve using a plastic syringe, a ball, and a 5 Volts DC micro servo motor to regulate the air pressure blown into the mouthpiece. The ADWI fingers are meticulously crafted using plastic pen barrels, thrust tubes, and metallic springs to simulate the actions of a human music player's fingers. Positioned to maintain all finger holes in an open state by default, the selective closing of specific holes is achieved by ten micro servo motors to produce a specific musical note. In a preliminary test, the ADWI prototype is programmed to perform the Nursery Rhyme "Twinkle, Twinkle, Little Star." While evaluating the sound output by hearing, it is evident that the proposed ADWI effectively generates all the necessary musical notes. However, the noise generated by the air blower and micro servo motors introduces interference, impacting the clarity of the produced musical notes. Consequently, it is planned to integrate a noise reduction mechanism as part of future work.

Desain dan Realisasi Alat Ukur Kadar CO2 Portabel dengan Notifikasi Suara Berbasis Mikrokontroler Arduino

Increasing levels of carbon dioxide (CO2) in the environment is a global issue that has an impact on climate change and air quality. Easily accessible CO2 measurement is important for monitoring and mitigating these impacts. This research aims to design and realize a portable CO2 level measuring instrument with sound notifications, using an Arduino microcontroller. The method used in this study is the development of microcontrollers. CO2 analyzers are designed using CO2 sensors, microcontrollers and sound output modules. Data processing and calibration are performed to ensure measurement accuracy. Tests are conducted at various locations to assess the performance of the tool in real conditions. This portable device is integrated with an audible notification system that provides immediate alerts to users when CO2 levels exceed unnatural limits. Concern for urban communities efforts to increase awareness and response to adverse air conditions, especially in open spaces and urban environments. The results showed that portable CO2 analyzers were able to measure CO2 levels with good accuracy according to the specifications of the components used. The sound notification system works to provide alerts in various conditions. Portability, ease of use make this tool useful for individuals and simple to carry to monitor and respond to changes in air quality.

Design of a Rice Weighing Tool with Sound Output Using Arduino Uno

Technological developments are currently growing increasingly widespread. This causes conventional equipment to be replaced with more sophisticated and fully automated equipment. This research aims to implement the design of a rice-weighing device with sound output using Arduino Uno. Meanwhile, the benefit you get is knowing the weight of the rice to be weighed and being able to simplify the process of selling rice for traders who sell rice. The research method for this tool uses input, output, and control processes. The load cell functions as an input that calculates the weight, the Arduino functions as a controller for all circuits, and the player and LCD are outputs that display prices. This rice weighing tool is designed in the form of a digital scale which aims to simplify the process of reading the weight of rice on the scale. The test results of this digital scale are that when the weight of rice is above 500 grams, this tool produces a sound output and displays the total price according to the importance of the rice.

Acoustical verification of binaural features in hearing aids

Hearing aid verification systems are designed to verify sound pressure levels in a patient’s ear canal, as well as ensure hearing aid features are performing to company specifications. In addition to verifying sound output, verification systems can analyze frequency specific compression, prescription targets, directional microphones, noise reduction performance, etc. However, current verification systems are unable to verify several advanced digital signal processing (DSP) features that companies have included in their hearing aids over the recent years. Particularly, binaural features which require both hearing aids to be analyzed simultaneously to measure interaural cues. Here, interaural cues were analyzed from recordings made on an acoustic manikin in an anechoic chamber across various noise reduction and directional microphone features using open-fit and occluding coupling compared to an unaided condition. During data collection, settings in the fitting software did not always align to hearing aid coupling (i.e., open versus occluding dome conditions), an error likely to occur clinically. For some noise reduction hearing aid conditions, a large interaural level difference (ILD) was introduced to one hearing aid, distorting the sound source location. ILD cues measured here, across different DSP and coupling conditions, suggest verification protocols should include additional features, such as binaural measurements.

Acoustic enrichment trials using autonomous cameras on a Hawaiian coral reef

Playbacks of ambient sound from healthy shallow coral reefs, known as acoustic enrichment (AE), can attract fish larvae and potentially coral larvae to degraded or artificial reefs. Large-scale studies face power supply challenges and require less intensive in-person surveys of recruited larvae (≤500 μm) and fish. Here, we present a preliminary assessment of artificial structure deployments with AE, conducted between July and September 2023 in Kane’ohe Bay (Oahu, Hawai’i). The artificial structures were designed to attract herbivorous juvenile reef fish and subsequently suppress algal growth. The work is part of a future artificial reef construction project in Hawai’i where in-person surveys and frequent battery replacements are logistically challenging. The deployments consisted of one control and one treatment site 65 m apart, in 5 m water depth and 10 m from the natural reef. To document ecosystem responses, both sites use open-source burst-mode autonomous cameras, a directional vector sensor seafloor acoustic recorder, and hydrophones. A 3.8 kW-h NiMh battery supply powers sound output for three weeks during evening hours. We discuss preliminary evaluations of AE and the validity of using autonomous cameras in evaluating performance in terms of fish recruitment and algal growth. [Work sponsored by DARPA.]

The High Accurate Automatic School Bell Controller Based On Arduino Uno DS1307 I2C Real-time Clock

Education plays a crucial role in developing human resources with the necessary character and competence to meet the demands of the future Industrial 4.0 revolution. To ensure the effectiveness of the teaching and learning process, schools require supporting facilities and infrastructure. One such component is the school bell, which helps teachers notify students of daily schedules. As technology advances, some schools have adopted an automatic school bell as an alternative to traditional bells. These automatic school bells use Arduino microcontroller technology to ring at scheduled times, automatically improving accuracy and convenience. By utilizing sound output via an Arduino-based system, every created information can be easily delivered and reached. This study follows the System Development Life Cycle (SDLC) method, a widely used system development methodology encompassing hardware and software systems. The research successfully demonstrates an automatic school bell system capable of automatically producing notification sounds, optimizing electricity consumption, and generating precise sound frequencies during teaching and learning activities. The output voltage and current results at various parts of the automatic school bell system range from 4.17 to 5.90 volts and 488 to 602 mA, respectively. At the same time, power consumption achieved about 2.07 to 3.38 Watts. An automatic school bell system simplifies ringing the school bell as it seamlessly integrates with the scheduled timetable (software). As a result, the automatic school bell now rings automatically according to the pre-defined schedule, enhancing efficiency and ensuring timely transitions between classes and breaks.

An End-to-End Musical Instrument System That Translates Electromyogram Biosignals to Synthesized Sound

Abstract This article presents a custom system combining hardware and software that senses physiological signals of the performer's body resulting from muscle contraction and translates them to computer-synthesized sound. Our goal was to build upon the history of research in the field to develop a complete, integrated system that could be used by nonspecialist musicians. We describe the Embodied AudioVisual Interaction Electromyogram, an end-to-end system spanning wearable sensing on the musician's body, custom microcontroller-based biosignal acquisition hardware, machine learning–based gesture-to-sound mapping middleware, and software-based granular synthesis sound output. A novel hardware design digitizes the electromyogram signals from the muscle with minimal analog preprocessing and treats it in an audio signal-processing chain as a class-compliant audio and wireless MIDI interface. The mapping layer implements an interactive machine learning workflow in a reinforcement learning configuration and can map gesture features to auditory metadata in a multidimensional information space. The system adapts existing machine learning and synthesis modules to work with the hardware, resulting in an integrated, end-to-end system. We explore its potential as a digital musical instrument through a series of public presentations and concert performances by a range of musical practitioners.

Improving APT Systems' Performance in Air via Impedance Matching and 3D-Printed Clamp.

This paper presents a study on improving the performance of the acoustic piezoelectric transducer system in air, as the low acoustic impedance of air leads to suboptimal system performance. Impedance matching techniques can enhance the acoustic power transfer (APT) system's performance in air. This study integrates an impedance matching circuit into the Mason circuit and investigates the impact of fixed constraints on the piezoelectric transducer's sound pressure and output voltage. Additionally, this paper proposes a novel equilateral triangular peripheral clamp that is entirely 3D-printable and cost-effective. This study analyses the peripheral clamp's impedance and distance characteristics and confirms its effectiveness through consistent experimental and simulation results. The findings of this study can aid researchers and practitioners in various fields that employ APT systems to improve their performance in air.

AI Color Organ: Piano Music Visualization using Onset Detection and HistoGAN

The music visualization algorithm described in this study allows users to construct piano audio files using imported image files. This paper contributes to previous studies and designs of sonification by highlighting the effectiveness of utilizing onset detection in creating intuitive sonic changes. The audio-visual correspondences employed in this study could be expanded to many other syntheses and sample manipulation techniques. Translating visual information into sonic changes could yield many creative applications in music production, as it offers musicians a simultaneously optical and auditory production experience. This approach to audio manipulation also increases the unpredictability of the sound output, which could be appealing to experimental musicians seeking to control sounds with the visual structure of artworks that they enjoy, as opposed to precise parameters. It is looking forward to seeing creative implementations of the techniques in audio-visual artworks, music production tools, and interactive multimedia systems. These results shed light on guiding further exploration of AI composing.

Patient-centricity: Research's new shibboleth?

Patient-centricity: Research's new shibboleth?

Using audio content and emotional response to predict soundscape perception through machine learning

This study is concerned with utilizing machine learning techniques for predicting soundscape perception by identifying the audio content of soundscapes and linking it with people's reported emotional responses. This research goal required developing an environmental sound classification model; however, the capabilities of these algorithms have some significant drawbacks. Supervised learning algorithms need a large number of labelled audio samples for each sound category. Given that a model for classifying environmental sound must be trained using a wide range of sound sources, this presents a substantial problem for developing a robust model that generalizes well to different environments. We prepared a convolutional neural network (CNN) based classifier; however, to tackle the limitations, we used musical instruments for the training dataset rather than environmental sound sources and optimized the neural network for this task. Based on how closely the soundscapes' audio content resembled the musical instruments in the dataset, CNN classified the soundscapes' audio content. We then conducted an online soundscape perception survey to evaluate participants' emotional responses to numerous soundscape clips. We prepared a feedforward neural network, which used the sound classification model's audio content output with the survey data to create a model for predicting people's responses to different soundscapes.

Deskripsi Kualitatif Masalah Perawat dalam Melakukan Auskultasi di Ruang Perawatan Intensive Care Unit

This study aims to analyze the problems of nurses in conducting auscultation in the intensive care unit. The research method used is descriptive qualitative research. The results of the study found three main themes found in this study, including 1) the time used for auscultation was minimal due to the large number of nurses' tasks to be completed, 2) the stethoscope used should have a clear sound when used, 3) the stethoscope should be more flexible in shape so that it is accessible to in use. In conclusion, the problem nurses face in conducting auscultation examinations on critical patients is the need for a stethoscope that has a more precise sound output and is flexible in its use.
 
 Keywords: Auscultation, Intensive Care Unit, Stethoscope

Graph-guided Bayesian matrix completion for ocean sound speed field reconstruction.

Reconstructing ocean sound speed field (SSF) from limited and noisy measurements/estimates is crucial for many ocean acoustic applications, including underwater tomography, target localization/tracking, and communications. Classical reconstruction methods include deterministic approaches (e.g., spline interpolation) and geostatistical methods (e.g., kriging). They exhibit a strong link to linear regression and Gaussian process regression in machine learning (ML) literature, by uniformly viewing them as supervised regression models that learn the mapping from the geographical locations to the sound speed outputs. From a unified ML perspective, theoretical analysis indicates that classical reconstruction methods have several drawbacks, such as the sensitivity to noises and high computational cost. To overcome these drawbacks, inspired by the recent thriving development of graph machine learning, we introduce graph-guided Bayesian low-rank matrix completions (LRMCs) for fine-scale and accurate ocean SSF reconstruction. In particular, a more general graph-guided LRMC model is proposed that encompasses the state-of-the-art one as a special case. The proposed model and the associated inference algorithm simultaneously exploit the global (low-rankness) and local (graph structure) information of ocean sound speed data, thus striking an outstanding balance of reconstruction accuracy and computational complexity. Numerical results using real-life ocean SSF data have demonstrated the encouraging performances of the proposed approaches.

Application Research of Pulse Vibration High-Frequency Voltage Injection Method Without Speed Sensor in New Energy Vehicles

The high-frequency voltage injection method of pulse vibration in the range of zero/low speed to medium-high speed has to be demonstrated for new energy vehicles., because it is very necessary and necessary to control the safety performance of the whole vehicle without speed sensor. The permanent magnet synchronous motor starts slowly to circle when the clean - energy vehicle cranked, and the correctness of the rotor’s startup position identification is significant. In order to achieve high-performance control of permanent magnet synchronous motor without speed sensor, this paper focuses mainly on how to estimate the rotor position of permanent magnet synchronous motor by amplifying the mathematical model of the motor. The high-frequency mathematical model of the permanent magnet synchronous motor’s voltage parameters are attained in the process of maintaining the motor’s preoperational position to address the problem of self-adaptability between the injected voltage and the likely phase current. The initial position identification of the rotor of a permanent magnet synchronous motor can be achieved by optimizing the adaptive method, and the pulse vibration highfrequency voltage anesthetic method also shows better efficiency and safety when the motor achieves a stable start and has sound output torque. The struggling to retain adaptive measurement device vibration high frequency voltage injection approaches is used by the light-duty low-speed new energy vehicle, which may minimize the mechanical speed sensor after becoming damaged, save the cost and improve the compactness of the electric vehicle space design, which is conducive to solving the situation of energy shortage in my country and alleviating environmental pollution. This is in line with the future development concept of society.