Audacity Software Research Articles

Acoustic voice assessment reliability in varying reverberation times

Objective: Acoustic voice and speech assessment is a non-invasive and cost-effective tool for the clinic and the laboratory. However, the effect of room environment can impact the voice and speech metrics. This study investigates the threshold levels of simulated reverberation times above which acoustic measures become unreliable for voice quality assessment. Methods: Fifteen male and female subjects were recorded producing the sustained /a:/ vowel three times in a sound booth. Using Audacity software, the recordings were mixed with various simulated reverberation levels (T30). Acoustic measures related to voice quality assessment—such as shimmer, jitter, Cepstral Peak Prominence (CPP), and Harmonics-to-Noise Ratio (HNR)—were estimated for both original and reverberation-affected recordings. Statistical analyses were performed to determine significant differences in these measurements across the different reverberation levels. Results/Conclusions: The analysis demonstrated that CPP and jitter were more robust against high reverberation levels, showing high T30 threshold values, while shimmer and HNR were more vulnerable to reverberant rooms with low T30 threshold values. The outcomes recommend specific reverberation thresholds in clinics and recording environments for accurate acoustic measurements. Identifying these reverberation limits aids in optimizing recording environments and establishing standard room conditions for reliable acoustic voice assessments.

Using Sundanese Musical Instrument and Audacity Software to Learn About Sound Waves

Integrating local culture into classes can build meaningful experiences for the students. Suling is a musical instrument originating from West Java’s dominant Sundanese culture and can be an alternative learning medium for teaching sound wave subjects. Using technology can facilitate understanding concepts for students. The Audacity software can help students analyze the spectrum and frequency of the sound produced by Suling. This study aimed to investigate the measurement of the frequency and spectrum of Suling with four and six holes and to analyze the potential for integrating local culture and technology in science learning. The type of research was descriptive to provide an overview of a symptom, event, and actual situation. We used a microphone and Audacity on the computer and each musical instrument in Suling. The study’s results showed that spectrum analysis has a similar pattern in Suling four and six holes and almost had similar frequencies. Local culture has the potential to be implemented in science learning, and technology facilitates students’ understanding of concepts. Suling and Audacity can be used as a learning media for a junior high school practicum on a sound wave subject. Keywords: Sundanese Musical, Instrument and Audacity Software, Sound Waves

Sonification of plantar pressure in runners with and without pain after running practice

PurposeHumans interact with the environment using sensory channels. Although vision is the main sensory channel, the auditory channel is excellent for learning when trained. Movement learning via auditory inputs requires sound analysis, such as sonification.MethodsData on peak plantar pressure from 43 recreational runners were collected using Flexinfit resistive insoles. Participants wore Run Falcon 1.0 (Adidas) running shoes and were categorised into four groups: without pain; spine or hip pain; thigh or knee pain; and leg, ankle, or foot pain. Participants responded to whether they presented pain and whether it was related to running (training or races). Sonification data were collected using the TwoTone software. We used the C note in the first octave to transform numerical data into sounds according to the pressure magnitude. The sound file was decomposed using the Audacity software into a spectrogram illustrating the main frequency components and their amplitudes.ResultsThe spectrogram made it possible to identify qualitative differences between the runners with and without pain after running. The frequency spectrum showed that some frequencies had greater sound intensity in runners without pain.ConclusionsOur results indicated differences between runners with and without pain after running using sonification. The frequency spectrum also indicated a difference in the sound intensity produced between the groups at specific frequencies.

Comparison of Arterial Stiffness among Prehypertensive and Normotensive Subjects using Photo Pulse Plethysmography: A Pilot Study

Introduction: Increased arterial stiffness is a marker of Cardiovascular Disease (CVD), even before clinical signs and symptoms become evident. Hypertension is an established risk factor for CVD. However, recent studies have revealed increased arterial stiffness even among prehypertensives. Photo Pulse Plethysmography (PPG) is an efficient non-invasive, and cost-effective technique to measure arterial stiffness. Studying arterial stiffness using PPG can serve as a surrogate marker of Cardiovascular (CV) risk among prehypertensives. Aim: To compare arterial wall stiffness among prehypertensives and normotensives using PPG. Materials and Methods: This pilot study was conducted at the Sri Ramachandra Institute of Higher Education and Research, Chennai, TamilNadu, India from December 2022 to February 2023. The study population included 10 non diabetic prehypertensives and 10 normotensives, aged between 30- 50 years, with normal lipid profiles. The peripheral pulse was recorded using a PPG module and digitised using AUDACITY software. The Arterial Stiffness Index (SI) was calculated and compared between the two groups. The correlation between anthropometry and arterial SI was also determined. Pearson’s correlation test was used to assess the association using Statistical Package for Social Sciences (SPSS) version 24.0. Results: The SI was found to be higher in prehypertensives compared to normotensives, and this difference was statistically significant (p-value=0.04). SI showed a positive correlation with increasing Blood Pressure (BP) and anthropometric variables (Body Mass Index [BMI] and Waist-Hip Ratio [WHR]; r=0.2 and r=0.15, respectively); however, no significant relationship was observed among these variables. Conclusion: This study concludes that the SI, an important CV risk marker, shows a significant increase in prehypertensive subjects compared to normotensive subjects. However, SI showed mild positive correlation with BP and other anthropometric measurements, though not statistically significant.

Experimental Analysis on Performance of Speech Utterance recognition using AI Models

In Automated speech recognition of the system performance is crucial and important to satisfy multiple requirements of HMI and, more recently, even in IoT-related applications as well. Concurrently, there has been an increase in demand for detecting strong critical features derived from speech utterances. This paper presents a performance of the developed machine learning algorithms with respect to audio digit speech recognition and classification. The prepared dataset contains a free range of words (from 1 to 10) from speakers of different age groups. The Audacity software used for preprocessing the audio files that includes removal of noise included in the signal and trimming the silence on either side of the word utterance. audio signal sampled at fs = 48kHz.We have developed four AI Models to recognise the word utterances. Audio signals are processed separately and derived two unique feature sets that includes statistical features set and singular values by performing SVD related to word utterances. The cepstral values for each utterance are obtained from state-of-the-art MFCC. Variance-covariance matrix is calculated from the generated MFCC matrix. The diagonal values which form the variance are recorded and denoted as feature set-1 for the word utterance and inputted to the machine learning algorithms. Performance matrices of the developed models are recorded. To keep the computational bottleneck associated with the use of feature sets to minimum, dimensionality reduction is carried out by applying singular value decomposition to the extracted MFCC matrix. The derived set of singular values ​​considered as feature set-2 is used to train and test the developed AI models with a ratio of 70:30. We presented and discussed the performance and results produced by MLP, KNN, SVM, Random Forest algorithms. In comparison, MLP and Random Forest were found to show excellent performance on both feature sets with 100% training accuracy and 99% test accuracy.

Spectrum Analysis of Sound Wave Recordings with Dolphinear type DE200 Based on Distance and Frequency Variations in Mahakam River Using Audacity Software

Dolphinear is an instrument for monitoring sound wave signals underwater. This study aims to see how the results of sound recording by Dolphinear type DE200 based on variations in distance and frequency of the sound source using the Audacity Software. In this study, the sound source will be generated through a waterproof speaker with a frequency variation of 100 Hz to 20 kHz. The distance between the sound source and the dolphinear is also varied from 1 to 5 meters. Audacity software is used to generate, record, and obtain the spectrum of the recorded audio sound signal. Based on the spectrum of the sound recorded by the DE200 dolphinear, frequency peaks close to the source frequency can be detected in recording using a 500 Hz sound source, but the main frequency peaks in the spectrum are difficult to detect in recording using sound sources above 500 Hz. In this study, it was also found that there is a limit to the recording ability of the dolphinear DE200 for frequencies above 18 kHz which is indicated by a decrease in intensity at that frequency.

Using Audacity Software to Enhance Teaching and Learning of Hearing Science Course: A Tutorial

Using Audacity Software to Enhance Teaching and Learning of Hearing Science Course: A Tutorial

Optimization of Ambient Acoustics in Los Angeles Restaurant by Material Selection

This paper explores the acoustic characteristics of Hai Di Lao Hotpot restaurant in the Los Angeles area and utilizes noise reduction technology to improve the acoustics of the restaurant in the modeling of ODEON software. First, 5 questions are designed to collect satisfaction level from eaters in the restaurant, and 12 different audio recordings are collected in the different locations of the restaurant. According to the analysis of results of questionnaire by Excel and decibel detection by Apple Watch, the improvement of acoustic environment is proven to be necessary to conduct in this restaurant. The collected audios tracks are then processed in the Audacity software to ensure that the sounds are close to sounds people heard in the restaurant as much as possible and the sound collection equipment (iPhone) won’t negatively affect the quality of audio too much. Then, an extant model in the library of ODEON software is chosen, and audios collected in the restaurant are inserted as audios for the chosen model. Some places in the model are also determined to place receivers. After that, by replacing original building materials in the model by materials that has better sound insulation or better sound concentration effect, the acoustic environment in the model is adjusted. By analysis provided by ODEON software, the audios after material adjustment are proven to be better with the change of building environment.

ANALISIS AKURASI PENERAPAN SOFTWARE AUDACITY DALAM MENENTUKAN NILAI FREKUENSI PADA PRAKTIKUM PIPA ORGANA

An organ pipe is a tool that uses an air column to produce sound. This research on organ pipes has the main goal, namely to determine the resonant frequency produced from each tone. The working principle of this research is to move the piston to produce the highest tone. The frequency obtained from manual calculations is in accordance with the existing theory, where the frequency and pipe length are inversely proportional. The relative frequency error in Audacity Software with the calculation results shows a small number, namely 1.08%, which means that the result has a high degree of accuracy.

Analyzing and Comparing Frequency of the Birds Sound Spectrum using Audacity Software in Practicum Activity

In the science learning process especially sound waves concept, experiments are needed that can help someone in gaining a meaningful learning and using technology. In this study, the aim is to analyze and compare the bird sound frequency assisted by Audacity software. The subjects used are three different bird sound (Murai Batu’s sound as the main subject while the Love Bird and Kenari’s sound as the compared subject). The implementation of this study uses several tools such as a microphone, Audacity software on a laptop and bird sounds. This experiment was carried out by bringing the microphone closer to the bird with 15 cm, so that the sound was captured by the microphone, then transferred to the laptop and read by the Audacity software. Furthermore, the data recorded in Audacity were analyzed. From the results of the study, it can be concluded that combination of bird sounds and audacity tools can be used in practicum, can read and capture bird sound waves effectively in analyzing and comparing the bird sound frequency and spectrum in the software. Thus, it tends to be utilized as one of the learning media in practicum on sound wave material at secondary school.

A forced cough sound based pulmonary function assessment method by using machine learning.

Pulmonary function testing (PFT) has important clinical value for the early detection of lung diseases, assessment of the disease severity, causes identification of dyspnea, and monitoring of critical patients. However, traditional PFT can only be carried out in a hospital environment, and it is challenging to meet the needs for daily and frequent evaluation of chronic respiratory diseases. In this study, we propose a novel method for accurately assessing pulmonary function by analyzing recorded forced cough sounds by mobile device without time and location restrictions. In the experiment, 309 clips of cough sound segments were separated from 133 patients who underwent PFT by using Audacity software. There are 247 clips of training samples and 62 clips of testing samples. Totally 52 features were extracted from the dataset, and principal component analysis (PCA) was used for feature reduction. Combined with biological attributes, the normalized features were regressed by using machine learning models with pulmonary function parameters (i.e., FEV1, FVC, FEV1/FVC, FEV1%, and FVC%). And a 5-fold cross-validation was applied to evaluate the performance of the regression models. As described in the experimental result, the result of coefficient of determination (R2) indicates that the support vector regression (SVR) model performed best in assessing FVC (0.84), FEV1% (0.61), and FVC% (0.62) among these models. The gradient boosting regression (GBR) model performs best in evaluating FEV1 (0.86) and FEV1/FVC (0.54). The result confirmed that the proposed method was capable of accurately assessing pulmonary function with forced cough sound. Besides, the cough sound sampling by a smartphone made it possible to conduct sampling and assess pulmonary function frequently in the home environment.

Analisis Percobaan Superposisi Gelombang Suara Menggunakan Software Audacity

Superposition of waves experiment in physics subject need more innovation to dig up student knowledge about the essential of waves in physics. Such innovation is using Audacity software for analyze it. The purpose of this study is to analyze the superposition of sound waves using Audacity software in the wave superposition experiment. The method used is to prepare tools and materials, namely PC/laptop, 250 Hz, 1 kHz audio files and Audacity Software. Then, 250 Hz and 1 kHz audio is sampled in one wave using Audacity after which each audio sample is imported twice and then combined with Audacity software and saved. This is done for different audio frequencies as well. Then, the results of the merger are opened with Audacity and then analyzed and compared with the initial wave. And the resulting superposition of two 250 Hz waves produces an amplitude of twice and 250 Hz and 1 KHz is produced over a 4 ms wave period and the constructive and destructive wave amplitudes depend on the phase of the two waves. Thus, wave superposition experiments using Audacity software facilitate the analysis of superposition results and characterize the period and amplitude properties of waves.

AI Based Diagnosis of Pneumonia.

Pneumonia is a lung infection caused by bacteria, viruses and fungi. In this infection, the air sac (alveoli) of the lungs gets inflamed and breathing becomes difficult which causes mild to severe illness among people. They are diagnosed by performing chest X-ray, blood test, pulse oximetry. Pneumonia can also be identified using lung sounds that are recorded in the digital stethoscope. In this proposed work, a software is developed to diagnose pneumonia from the lung sound using gradient boosting algorithm. Lung sounds give enough symptoms for pneumonia identification. Lung sounds are recorded by doctors using Electronic Stethoscope. The recorded lung sounds are processed using audacity software. This software separates the required sound from unwanted noises. The healthy individual’s audio files are labelled as 0 and the pneumonia patient's audio files are labelled as 1 for training the algorithm. During diagnosis study and the performance evaluation with various machine learning algorithms like support vector machine and k-nearest neighbours (KNN) algorithms, it was observed that the gradient boosting algorithm exhibits good identification property with 97 percent accuracy. This proposed method also reveals excellent diagnoses of pneumonia over other artificial intelligence and deep learning techniques. This method can also be used to predict Covid affected lungs sounds.

Acoustic change complex using short duration stimuli in normal hearing children: temporal resolution and frequency discrimination

Objective Acoustic Change Complex (ACC) is a cortical auditory evoked potential elicited in response to a change in an ongoing sound. Since it is supposed to reflect auditory discrimination at the cortical level, recording of this potential has recently gained much attention. From a technical standpoint, the stimulus used should be long enough to accommodate the needed change. This research addresses the development and standardization of short duration tonal stimuli which can be implemented in most of the Evoked Potential (EP) equipment used in regular Audiology clinics. Methods Short duration tonal stimuli (500 msec.) were generated and edited using Audacity software. Temporal change was done using gap-in-tones stimuli (6, 10, 30 and 50 msec. in 1000 Hz tone). Frequency change was represented by frequency pairs (2%, 4%, 10% and 25% change from 1000 Hz base frequency). The developed stimuli were then used to generate ACC potential in 41 normal hearing children ranging in age from 2 to 10 years. A comparison was held between ACC response recorded using the different stimuli in reference to percent identifiability, morphology, latency and amplitude measures. Results Gap-in-tones at 10 msec. and 4% frequency change could elicit ACC response in 100% of subjects. ACC had the same morphology of the onset response in the majority of subjects, with longer latency and smaller amplitude. ACC amplitude was consistently affected by magnitude of change. Conclusion ACC was successfully recorded in 100% of normal hearing children using the developed short duration tonal stimuli for temporal change (10 msec.) and frequency change (4%). These stimuli can be uploaded in clinical EP equipment. ACC amplitude could be a better indicator of cortical discrimination compared to latency.

Determining Gravitational Acceleration Accurately and Simply

There are several ways in the literature to determine the value of gravitational acceleration. we will present a way that allows us to determine the we used an audio plug (3.5-mm jack) that can be reused from types of plugs can also be purchased and are very cheap. In this article, a computer speaker or microphone that are damaged. These value of gravitational acceleration very accurately using every-day materials. For this, we will use an electromagnet, a coil, a steel sphere, a speaker, an audio cable (3.5-mm jack), a direct current power supply, connecting wires, a computer, and the Audacity software.

Audacity Software Analysis In Analyzing The Frequency And Character Of The Sound Spectrum

In the process of learning physics, experiments are needed that can help someone in gaining a deeper understanding of learning physics concepts and using technology in the learning process, especially learning sound waves. In this study, the aim is to be able to analyze the sound frequency with the help of Audacity software. Subjects used are 5 different cat sounds. The implementation of this research uses several tools such as a microphone, Audacity software on a laptop, and 5 cat sounds. This experiment was carried out by bringing the micro hope closer to the cat with 5 cm so that the sound was captured by the microphone which would later be transferred to the laptop and read by the audacity software. Furthermore, the data recorded in audacity were analyzed. From the results of the study, it can be said that a tool that can be used in practicum and can read and capture sound waves is effectively used in analyzing sound frequency, spectrum in the application of sound learning so that it can be used as one of the learning media in practicum on sound wave material at Junior high school.

Design of wireless audio transmission system for college English language teaching

In the past, the use of wireless microphone was affected by overload noise, resulting in incomplete transmission of teaching content. In order to solve this problem, a wireless audio transmission system design for College English language teaching is proposed. The overall architecture of SEP6010 wireless voice system is designed, which is output by PWM channel to complete voice playback. UDA1341TS low-power stereo analog-to-digital converter is used to control audio transmission. The voice circuit is designed by adding clock signal or internal programmable clock. The A/D conversion module is used to amplify the collected signal, and the original voice signal is restored through the audio playback module. MATLAB is used to simulate the process of encoding, decoding and filtering. According to CVSD quantization integral coding algorithm, the quantization noise is reduced to a given allowable value. Start Audacity software to complete wireless audio transmission. The experimental results show that the highest transmission teaching content integrity of the system under single frequency input is 98%, and the highest transmission teaching content integrity under mixing input is 93%.

Development of Simple Teaching Aid on Resonance Topic Using Audacity Software as Learning Media

This study aims to develop a simple prop of resonance topic using audacity software. The research was conducted based on the model from Borg and Gall, which involved only five main steps: analyzing the developed product, developing the initial product, expert validation and revision, small-scale field trials and revisions, and large-scale trials and final products. The small-scale and large-scale feasibility tests were given to 29 students of SMAN 5 Palu Class XI IPA6. The product quality data obtained were analyzed using a descriptive analysis from quantitative data into qualitative, then the average quality score was processed using category criteria. In the analysis results, the overall average score of media experts is 2.97, categorized as “Good”. The overall average score from material experts was 3.33, categorized as “Very Good”. While the average analysis result of the overall small-scale trials was 3.35, categorized as “Very Good”, and the result of the overall large-scale trials was 3.39, categorized as “Very Good”. The overall average score obtained in the transformation in table 2 shows that the simple teaching aid on resonance topic using the Audacity software developed by the researcher was feasible to be used as a medium for learning physics in the classroom.

Vocalization and other behaviors indicating pain in beef calves during the ear tagging procedure

Vocalization and other behavior signals are used as tools to assess animal welfare in beef calves. This paper aimed to compare vocal parameters and behavior signals expressed by beef calves submitted either to ear tagging procedure for identification (Effective Tagging - ET) or to a human touch on the ears (Simulated Tagging - ST), considering calf sex and age. A total of 52, 30 male and 22 female, 91.3 ± 28.1 d-old taurine beef calves participated in the study, in Santa Catarina, Southern Brazil. Calves were randomly divided into two treatments (ET and ST) and recorded for 1 minute after the beginning of the stimulus for both ET and ST situations, as this was the total time animals were restrained. We analysed the immediate vocal and behavioral responses to the procedure, following regular handling procedures used on the farm. Vocal data was further analysed using specific audacity software and behavioral signs were counted. More animals in the ET treatment vocalized during the trial (14 and 5 calves, respectively), with a higher average number of vocal calls (1.7 and 0.3 calls/animal), as well as of head movements (7.8 and 4.0 movements), tail flapping (56.1 and 29.8) and leg movements (28.4 and 16.4). Male vocalizations were longer than female (2.07 and 1.61 s), with higher fundamental frequency (249.6 and 178.6 Hz). Additionally, older calves vocalized with higher fundamental frequency (241.0 and 212.8 Hz) and showed more head movements (6.5 and 5.3 occurrences) than younger ones. The results suggest that the vocalization characteristics associated with other behavior signals may be used as tools to assess pain in beef calves during invasive procedures such as identification handling.

A comparative study between single lead AD8232 heart rate monitor and standard electrocardiograh to acquire electrocardiographic data for cardiac autonomic function testing

Objectives: The present study was to develop and design a simple and low cost ECG setup for patient care. The device is a low cost and simple approach for acquiring ECG data. The present study mainly focuses on reliability and consistency for acquiring the ECG data. It should be simple to use, portable and low cost to implement. Methods: The following study was conducted between two groups of subjects; each group contains n=40 subjects. First the subjects were recruited to the department of physiology autonomic function laboratory and the demographic and anthropometric data was acquired. The subjects were allowed to rest for some time. Single lead ECG was obtained using AD8232 custom designed module and was connected to a laptop as signal was captured by audacity software and compared against a medical grade ECG monitor and the results were analyzed. Findings: From our study it is clearly evident that there is a strong positive correlation of ECG data obtained between AD8232 and standard clinically approved ECG monitor r=0.9 (p 0.001). Now it is clearly evident that we can use AD8232 module instead of standard ECG device for basic monitoring. Novelty: The new device developed successfully captured single lead ECG which is a low cost implementation around |2350 (table given in annexure). Capturing ECG with microphone input is quite new way of acquiring ECG signals. The new device was easy to set up, no special software is needed to acquire the signal runs on USB voltage which is 5v. The device is simple to use, open source hardware and consistent with the recordings when compared with the standard ECG monitor. The latest device can be configured in many ways for future applications using open source sound capturing software. Audacity open source software. Keywords: Portable ECG; single lead; USB; open source; AC; DC; AD8232; GPL