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Summary Objective Past literature indicates that vibrato measurements of singers objectively changed (i.e., vibrato rate decreased and vibrato extent increased) from 1900 to the present day; however, historical audio recording technology may distort acoustic measurements of the voice output signal, including vibrato. As such, the listener's perception of historical singing may be influenced by the limitations of historical technology. This study attempts to show how the wax cylinder phonograph system—the oldest form of mass-produced audio recording technology—alters the recorded voice output signal of modern-day singers and, thus, provides an objective lens through which to study the effect(s) of historical audio recording technology on vibrato measurements. Methods Twenty professional Western opera singers sang a messa di voce on the vowel [a] and on the pitch C4 for male singers and C5 for female singers, three times into a flat-response omnidirectional microphone and onto an Edison Home Phonograph simultaneously. The middle 1–3 seconds (6–10 vibrato cycles) of each sample was analyzed for vibrato rate, vibrato extent, jitter (ddp), shimmer (dda), and fundamental frequency for each recording condition (wax cylinder phonograph or microphone). Steady-state and frequency-modulating sinewave test signals were also recorded under the multiple recording conditions. Results Results indicated no significant effect of recording condition on vibrato rate (mean [standard deviation], cylinder: 5.3 Hz [0.5], microphone: 5.3 Hz [0.5]) and no significant difference was found for mean fundamental frequency (cylinder: 389 Hz [137], microphone: 390 Hz [137]). A significant main effect of recording condition was found for vibrato extent (cylinder: ±103 cents [30], microphone: ±100 cents [31]). Additionally, mean jitter (ddp) (cylinder: 1.22% [1.09], microphone: 0.24% [0.12]) and mean shimmer (dda) (cylinder: 9.40% [4.90], microphone: 1.92% [0.94]) were significantly higher for the cylinder recording condition, indicating more cycle-to-cycle variability in the wax cylinder recorded signal. Analysis of test signals revealed similar patterns based on recording condition. Discussion This study validates past scholarly inquiry about vibrato measurements as extracted from digitized wax cylinder phonograph recordings by demonstrating that measured vibrato rate remains constant during both recording conditions. In other words, vibrato rate as measured from historical recordings can be viewed as an accurate representation of the historical singer being studied. Furthermore, it suggests that the value of prior vibrato extent measurements from these acoustic recordings may be slightly overestimated from the original voice output signals produced by singers near the beginning of the 20th century (i.e., a narrow vibrato extent might have been numerically smaller on average). Increased jitter and shimmer in the wax cylinder recording conditions may be indicative of nonlinearities in the phonograph recording or playback systems

The demand for flexible, efficient, and self-powered cochlear implants applied to remedy sensorineural hearing loss caused by dysfunctional hair cells remains urgent. Herein, we report an acoustic core-shell resonance harvester for the application of artificial cochleae based on the piezo-triboelectric effect. Integrating dispersed BaTiOsub3/subparticles as cores and porous PVDF-TrFE as shells, the acoustic harvest devices with ingenious core-shell structures exhibit outstanding piezo-triboelectric properties (iV/isubioc/i/sub= 15.24 V,iDA/isubisc/i/sub= 9.22 mA/msup2/sup). The acoustic harvest principle reveals that BaTiOsub3/subnanocores resonate with sound waves and bounce against porous PVDF-TrFE microshells, thereby generating piezo-triboelectric signals. By experimental measurement and numerical modeling, the vibration process and resonance regulation of acoustic harvest devices were intensively investigated to regulate the influential parameters. Furthermore, the acoustic harvesters exhibit admirable feasibility and sensitivity for sound recording and show potential application for artificial cochlea.

This essay focuses on the career of Honorata “Atang” de la Rama on the popular sarsuwela and vaudeville stages during the period of American colonization in the Philippines. Through sound recording...

The use of machine learning technologies to process large quantities of remotely collected audio data is a powerful emerging research tool in ecology and conservation.We applied these methods to a field study of tinamou (Tinamidae) biology in Madre de Dios, Peru, a region expected to have high levels of interspecies competition and niche partitioning as a result of high tinamou alpha diversity. We used autonomous recording units to gather environmental audio over a period of several months at lowland rainforest sites in the Los Amigos Conservation Concession and developed a Convolutional Neural Network‐based data processing pipeline to detect tinamou vocalizations in the dataset.The classified acoustic event data are comparable to similar metrics derived from an ongoing camera trapping survey at the same site, and it should be possible to combine the two datasets for future explorations of the target species' niche space parameters.Here, we provide an overview of the methodology used in the data collection and processing pipeline, offer general suggestions for processing large amounts of environmental audio data, and demonstrate how data collected in this manner can be used to answer questions about bird biology., The use of machine learning technologies to process large quantities of remotely collected audio data is a powerful emerging research tool in ecology and conservation. We used autonomous recording units to gather environmental audio over a period of several months at lowland rainforest sites in the southeastern Peruvian Amazon and developed a Convolutional Neural Network‐based data processing pipeline to detect tinamou (Tinamidae) vocalizations. The resulting occurrence dataset is comparable to similar metrics derived from an ongoing camera trapping survey at the same site, and it should be possible to combine the two datasets for future explorations of the target species' niche space parameters.

MPEG surround is one of the most popular multichannel audio coding standards used today. In producing quality sound, there are several parts that are influential, but those that are directly related to sound reproduction, one of which is the method of downmixing, mixing the right channels will improve the quality of the sound produced. Because this research is closely related to data computing, the Matrix Laboratory (MATLAB) application is used. There are 2 stages carried out in the MATLAB application, namely the encoding and decoding process. In the encoding process in MATLAB, each audio channel is set according to a previously designed scheme. The results of this encoding are then decoded, so that the ODG value of each tested audio channel is obtained. In his presentation, the design and analysis of several domnmixing schemes was carried out. There are 5 schemes tested and to determine the performance of each scheme, these schemes are tested at high bitrates, from the range of 1000 Kbps to 2000 Kbps. Based on the test, it was found that the effect of increasing the bitrate is directly proportional to the resulting audio quality. During testing Scheme-5 has a better level of stability among all downmixing schemes and the average percentage increase in Objective Difference Grade (ODG) for all audio samples is 9.6927 %., MPEG surround merupakan salah satu standard pengkodean audio multikanal yang populer digunakan saat ini. Dalam menghasilkan suara yang berkualitas, ada beberapa bagian yang berpengaruh, namun yang berkaitan langsung dengan reproduksi suara, salah satunya adalah metode dalam melakukan downmix, percampuran kanal yang tepat akan meningkatkan kualitas dari suara yang dihasilkan. Dikarenakan penelitian ini berkaitan erat dengan komputasi data, maka digunakanlah aplikasi Matrix Laboratory (MATLAB). Ada 2 tahap yang dilakukan pada aplikasi MATLAB, yaitu proses encoding dan decoding. Pada proses encoding di MATLAB, disetting setiap kanal audio sesuai dengan skema yang telah dirancang sebelumnya. Hasil dari encoding ini kemudian di decode, sehingga didapatkan nilai ODG dari setiap kanal audio yang diujikan. Pada pemaparannya dilakukan perancangan dan analisis terhadap beberapa skema domnmixing. Terdapat 5 skema yang diujikan dan untuk mengetahui performansi dari tiap skema, skema tersebut diuji pada bitrate tinggi mulai dari range 1000 Kbps sampai dengan 2000 Kbps. Berdasarkan pengujian didapati bahwa pengaruh kenaikan bitrate berbanding lurus terhadap kualitas audio yang dihasilkan. Selama pengujian Skema-5 memiliki tingkat kestabilan yang lebih baik diantara semua skema downmixing dan rata-rata persentase kenaikan Objective Difference Grade (ODG) untuk seluruh sampel audio adalah 9,6927 %.

The article provides an interpretation of the most commonly used terms and terminological components, provides practical recommendations for standartization of variance of terms, which will be useful to experts when analyzing the results and preparing expert conclusions.

Urban sound maps are audio-visual representations of cities created by associating sounds and urban landmarks on a digital geographic map. Fusing cartography and audio recording, urban sound maps p...

Smart devices with the capability to record audio can create a trade-off for users between convenience and privacy. To understand how users experience this trade-off, we report on data from 35 interview, focus group, and design workshop participants. Participants' perspectives on smart-device audio privacy clustered into the pragmatist, guardian, and cynic perspectives that have previously been shown to characterize privacy concerns in other domains. These user groups differed along four axes in their audio-related behaviors (for example, guardians alone say they often move away from a microphone when discussing a sensitive topic). Participants surfaced three usage phases that require design consideration with respect to audio privacy: 1) adoption, 2) in-the-moment recording, and 3) downstream use of audio data. We report common design solutions that participants created for each phase (such as indicators showing when an app is recording audio and annotations making clear when an advertisement was selected based on past audio recording).

The purpose of the article is to characterize the principles of sound recording with microphones in the context of the acoustic spatial features of concert halls, which are an important component in positioning the activities and creative directions of "purism", "individualism" and "realism" in sound engineering. The methodology consists of the use of analytical, historical, and cultural methods, which made it possible to identify and characterize the technological foundations of sound recording using the example of sound engineers. The scientific novelty of the work lies in the fact that for the first time in Ukrainian science the principles of microphone sound recording in the context of acoustic spatial features and creative directions of sound engineering "purism", "individualism" and "realism" were defined and characterized. Conclusions. In the work, the data on the spectral response of the frequency range, the stereophonic effect, musical and timbre balance, and the spatial impression of the acoustics of concert halls were determined. The principles of application of multi-microphone technique in instrumental, orchestral, and rock music are revealed; outlined the creative potential of the directions "purism", "individualism" and "realism". in sound engineering. In terms of current cinematic trends and contemporary popular music culture, we hear and become accustomed to exaggeratedly colorful and rich, often "electronic" sound. Since the listener is the ultimate link in the entire recording industry, it is necessary to recognize landmarks in sound engineering aimed at the tastes of the majority.

This study aims to investigate consonant and vowel changes in the Brummie accent as compared with the ones in the standard variety of English through a comparative descriptive study. The investigation is based on an audio recording conversation and an extract of a TV show film; in addition to a questionnaire administered to 40 second year students of Master degree of linguistics from the English section of Ibn Khaldoun University, after they have been exposed to both the audio recording and the film extract. This is to gather information about their attitudes towards the aforementioned changes’ effects. Thefindings of the current study reveal the existence of great alterations in the articulation of vowel and consonant sounds in Brummie accent, which may differ from the norms that govern the standard variety of English. The outcomes of the audio recording and video extract as well as the gathered data from students’ questionnaire point out negative effects on learners’ clear perception of Brummie accent, which will undoubtedly lead to their fear of confronting serious communication problems when talking with UK citizens.

A previous study found that spatial release from masking (SRM) could be observed under virtual reverberant environments using a first order Ambisonic-based sound reproduction system, however, poor localisation accuracy made it difficult to examine effect of varying reverberation time on SRM. The present study follows on using higher order Ambisonics (HOA) to examine how benefits from SRM vary in different spatial acoustics. Subjective speech intelligibility was measured where four room acoustics:reverberation time (RT)= 0.7 s (clarity (C50)= 16 dB, 7 dB); RT= 1.8 s (C50= 8 dB, 2 dB) were simulated via a third order Ambisonic system with a 16 channel spherical loudspeaker array. The masker was played from 8 azimuthal angles (0, +-45, +-90, +-135, 180 degrees) while the target speech was played from 0 degree. The listeners are deemed to benefit from SRM if their intelligibility scores were higher when the masker comes from a different angle than that of the target. We found while listeners could benefit from SRM at C50 = 16 dB and 8 dB, the benefit starts to diminish at C50 = 7 dB, and listeners could no longer benefit from SRM at C50 = 2 dB.

A noise monitoring campaign has been performed in an urban park of Milan (Italy) called Parco Nord. The area of study is a large peri-urban park in the northern part of the city, characterized by wooded land rich in biodiversity and exposed to different sources and degrees of anthropogenic disturbances, such as road traffic noise and artificial light. The acoustic environment is rather complex due to the contemporary presence of different noise sources, leading to the difficult task of discriminating them in audio data. Due to these multifactorial characteristics, we evaluated different eco-acoustic indices in the attempt to derive a methodology to evaluate the potential of sound ecology indicators to discriminate the different types of sounds present in medium-large urban parks. Time series of about two-week recordings have been transformed into eco-acoustics indices and statistically analysed. The results show a redistribution of recordings into each cluster associated with different sound components and different period of the day. This allowed the identification of different degree of biophonic and/or anthropogenic activities throughout the day.

This paper presents and explores a robust deep learning framework for auscultation analysis. This aims to classify anomalies in respiratory cycles and detect disease, from respiratory sound recordings. The framework begins with front-end feature extraction that transforms input sound into a spectrogram representation. Then, a back-end deep learning network is used to classify the spectrogram features into categories of respiratory anomaly cycles or diseases. Experiments, conducted over the ICBHI benchmark dataset of respiratory sounds, confirm three main contributions towards respiratory-sound analysis. Firstly, we carry out an extensive exploration of the effect of spectrogram type, spectral-time resolution, overlapped/non-overlapped windows, and data augmentation on final prediction accuracy. This leads us to propose a novel deep learning system, built on the proposed framework, which outperforms current state-of-the-art methods. Finally, we apply a Teacher-Student scheme to achieve a trade-off between model performance and model complexity which additionally helps to increase the potential of the proposed framework for building real-time applications.

Virtual and laboratory-based design techniques can accelerate the development process over conventional prototype-and-field-test procedures. In car acoustics, the transmission of outside airborne noise into the cabin needs to be understood and managed. Here, we evaluate the accuracy of sound field recording and reproduction techniques for investigating the transmission of airborne noise into the driver's cabin of a car. Reference measurements of a real sound field, generated by a truck with idling engine to create a realistic scenario, were carried out in a semi-anechoic chamber. The reference sound field was recorded inside and around a test car. Additionally, a spatial recording of the reference sound field was carried out and used to reproduce the reference sound field over a loudspeaker array in a different, fully anechoic chamber, where the sound field was again measured inside and around the same test car. A comparison of the measured loudness inside the test car shows that this key parameter for sound quality could be reproduced rather faithfully over a loudspeaker array in a controlled testing facility.

Throughout history, music has been presented to the audience in different ways, and technology has played an essential role in shaping the forms of music consumption. Each innovative process has le...

Binaural system is an audio technology which relatively easy to apply these days. This was due to the growth in technology developments of the audio recording system. The application of this system is not well known in Indonesia. This was aligned with public assumption where Wayang Kulit performance are one of many unappreciated forms of arts in Indonesia. The main problem that occurred is that whether the binaural system conjoined with the Virtual Reality (VR) System can make the public more appreciate the art form of Indonesian Wayang Kulit. By using the theory of perception conjoin with the binaural technology, it can be assumed that the audience can have a new experience from the performance through the VR thus elevating their appreciation for the art itself. This research will be divided into three stages. The first stage focused on the application of the binaural system on Wayang Kulit Animation through VR system. The second stage will focus on the product assessment whether it can elevate the appreciation of the audience for the art itself. The third stage will focus on applying the binaural system on other Indonesian art form. This year, the research will begin at the first stage.

THE AIM OF THE PAPER There is emerging demand in several scientific areas for measuring human behaviour, attitude and cognitive processes. We live the golden ages of computational modelling in medical sciences, engineering, psychology and marketing. Computational social psychological observations (video recording, sound recording, sociometer, GPS etc.) enable us to investigate human interactions more deeply. This study gives an insight into the possibility of measuring team dynamics with computational techniques, based on interviews with experts. The aim of research is to reveal werther it is possible to advance measuring team dynamics with computational techniques? METHODOLOGY To investigate the topic of measuring team dynamics I use a multiparadigmatic sequential research design. In this paper I present an interpretative reveal study based on expert interviews. This is the primary, qualitative phase of the complete research and it serves as an input for the following functionalist phase. Data collection was based on a preset questionnaire and took place between November 2019 and March 2020 (Appendix 1). The interviews were semi-structured, which made it possible to enlarge knowledge by asking further questions. MOST IMPORTANT RESULTS Measuring team dynamics is still in its infancy and there is not enough focus on it within the organizations. While organizational development focuses on group processes, in daily activities of organizations observing and evaluating individual performance, motivating individuals is the main focus. Measuring team dynamics is often limited to self reported surveys and participant observation due to lack of time and budget. Computational measuring (webcamera, sound recording) is not widely spread. despite the fact that experts see it as a possible solution. RECOMMENDATIONS Computational techniques and machine learning make it possible to capture human interactions and exchanges, identify meaningful patterns and use them to predict important outcomes, to analyze complex team dynamic questions for organizational and HR managers, for trainers and organizational developers. Experts interviewed find it an important and desired, yet costly, complex and hard to decode solution.

This article uses the concept of phonography, defined as the representation of sonic events, to examine two of W.B. Yeats’s later plays, The Words upon the Window-Pane and A Full Moon in March. Each of these plays allegorizes its own genesis as a phonographic artwork, a sonic inscription designed to transmit the author’s voice. By asking whether text can serve as a conduit, they provide ample evidence of Yeats’s attachment to phonocentric thought. The Words anticipates Roland Barthes’s pronouncements on “the death of the author” by pessimistically deconstructing Yeats’s own phonocentric position. Its centrepiece is a corrupted séance that functions as a travesty of the play itself, enacting a mechanical medium through a spiritualist medium who seems to relay a recording of the voice of Jonathan Swift. While The Words registers a host of anxieties about mediation, social degeneration, and nullified authority, A Full Moon reconciles voice and inscription in the symbol of the singing severed head. This reconciliation is allegorized as a sacred marriage, a scripted ritual that involves an execution by beheading. The head’s song, which can be read as Yeats’s figure for the phonographic inscription, represents the magically immediate transmission of the poet’s voice to a posthumous audience.

Language was a means of communication between members of a single community, so that some of them would express to each other their ideas and thoughts, and a common characteristic of that society was defined, and the origin of the word was derived from (rhetoric, idle), if he repealed the matter and spoke about it, and the ancients knew it that language: (It is what expresses It contains all the people for their belongings). The ancients went in their definition of a language to the characteristics of their language with which they communicate, without referring to the Arabic language as a language among the living languages ​​that are circulating among them. Arabs and Arabs (whoever inhabited the country and its island, or uttered the language of its people), and to it returns the percentage of the Arabic language, which is one of the Semitic languages. Which spread in the Arabian Peninsula, and the writing came to denote what is in the minds of notables. This research presents a computer application that depends on human input to pronounce the Arabic letters The system consists of two phases, the first stage is the axis of creating a database for Arabic language characters and their storage locations, as well as the type of formulas for those letters when the initial processing was performed. The second stage is the process of comparing the entered letter from the text with the corresponding sound and placing it in a storage so that we can then process it. In the practical part of the research, we used a comparison between the results of four methods to obtain the least possible execution time with the least pauses in speech, which are the combinative method, the smoothing method, the method of nesting speech, and a hybrid method between smoothing and interfering together. We start by entering in the input text box and using the SpellLetter function, which we use for the purpose of processing and pronunciation, where the input is of three types, either it is a char, or it is an array of characters (String), or it is numbers between zero and nine Num), and in the case that the entry was not For these three types, the entry is wrong, for example, non-Arabic letters or special symbols, for example.,And if the entry was correct, each letter is taken with its accent. This means that we take two positions each time. Using Matlab (R 2018a) to build the proposed system and it was implemented using a computer. Portable running under the environment of the operating system (Microsoft Windows 10).

Agricultural machines (AMs) refer to equipment usually used in agriculture such as tractors, hand tools, and power tools. It reduces the labor work, increases farms produce, enhances goods quality, and reduces farming time and cost-saving. However, the faults in the fuel system, blades, engine of the AM will often result in degraded vehicle performance, compromising the vehicle’s efficiency and strength. To overcome these problems, fault detection algorithms are developed to identify the faults even before they occur with high classification accuracy. The deep convolutional neural network (DCNN) is a popular deep learning model that offers a high classification recognition rate, and it is widely adopted in similar fields for monitoring the health status of machines. Very few state-of-the-art works are available to identify the health state of agricultural machines using deep learning techniques and extracting the acoustic features from an audio recording. The acoustic signal-based agricultural machine health monitoring and fault prediction model using smartphones is a cost-effective option that is deployed in this proposed work. To optimize the network structure of the DCNN, this paper proposes a Levy flight optimization algorithm (LFOA). The DCNN-LFOA model is implemented on the smartphone’s on-board device (OBD) along with the health monitoring application. The LFOA algorithm minimizes the number of neurons in the DCNN hidden layer and the number of input features from the audio recordings and enhances the classification accuracy. The LFOA algorithm provides the optimal solution which is essential in developing a lightweight DCNN model to implement in the edge processor (smartphone). The experimental results prove that the proposed model gives improved accuracy for the six faults to be classified and serves as a new research model to identify the health condition of the vehicles.

Kazakh traditional music has been the research object for many scientists from Russia, Germany, Great Britain, Hungary, Japan, the United States, and other countries. In the 20th century, due to the establishment of Soviet power, the territory of Kazakhstan was closed for research by foreigners. Simultaneously, such a combination of events contributed to preserving materials collected before the Great October Socialist Revolution. Therefore, today it is vital for the World and Kazakh ethnomusicology to consider unknown materials and scientific sources. Various foreign archives contain materials unknown to Kazakh ethnomusicologists about Kazakh traditional music collected on researchers’ and traveler’s expeditions since the end of the XVIII century. Recordings of the German ethnographer-anthropologist R. Karutz were found in 2016 by the film crew of the Interstate TV and Radio Company “Mir”, and analyzed and published by the doctor of Art studies S. I. Utegalieva in the book” Turkestan collection of songs and instrumental pieces collected by R. Karutz (1905)”. These recordings prove that there are sources about Kazakh traditional music that can change the opinion about the historical significance of the Kazakh culture in the Central Asian region. The famous turcologist Efim Rezvan presented the records in the Pushkin Museum in St. Petersburg. It turned out that the original cylinders with authentic recordings are currently stored in the archive of the Berlin Museum of Visual Anthropology and Ethnology. This article reviews the documentary film "Road of People: The First Audio Recording of Kazakh Music", and sheds light on the possible prospects of studying the problem of research the Kazakh traditional music. Today, the Berlin Phonogram Archive contains samples of music from all over the world, the first recording dates back to 1900. The collection of wax cylinders by Richard Karutz is kept in the Department of Ethnomusycology, Visual Anthropology at the Berlin Phonogram Archive of the Ethnological Museum in Berlin. The collection is well preserved, and according to its curator Dr. Ricarda Kopal, there are 16 wax cylinders from Turkestan, an area of ​​now southern Kazakhstan, which R. Karuts crossed during his expedition. The film crew brought digital copies of the recordings to Almaty for further study. Kazakh and international scientists and performers, professors and doctors of sciences: S. Utegalieva, T. Togzhanov, A. Berdibay (Kazakhstan), I. Saurova (Karakalpak Autonomous Republic), R. Abdullaev (Uzbekistan) and others were involved to decipher, analyze, describe and evaluate the musical and artistic content of the recordings. The whole process was documented in the film, which was worked on by a whole team of professional journalists, the script was written by Timur Sandybaev and Askar Alimzhanov, directed by Kanat Yessenamanov.

Heart sound segmentation (HSS) aims to detect the four stages (first sound, systole, second heart sound and diastole) from a heart cycle in a phonocardiogram (PCG), which is an essential step in automatic auscultation analysis. Traditional HSS methods need to manually extract the features before dealing with HSS tasks. These artificial features highly rely on extraction algorithms, which often result in poor performance due to the different operating environments. In addition, the high-dimension and frequency characteristics of audio also challenge the traditional methods in effectively addressing HSS tasks. This paper presents a novel end-to-end method based on convolutional long short-term memory (CLSTM), which directly uses audio recording as input to address HSS tasks. Particularly, the convolutional layers are designed to extract the meaningful features and perform the downsampling, and the LSTM layers are developed to conduct the sequence recognition. Both components collectively improve the robustness and adaptability in processing the HSS tasks. Furthermore, the proposed CLSTM algorithm is easily extended to other complex heart sound annotation tasks, as it does not need to extract the characteristics of corresponding tasks in advance. In addition, the proposed algorithm can also be regarded as a powerful feature extraction tool, which can be integrated into the existing models for HSS. Experimental results on real-world PCG datasets, through comparisons to peer competitors, demonstrate the outstanding performance of the proposed algorithm.

Conversational assistants in the form of stand-alone devices such as Amazon Echo and Google Home have become popular and embraced by millions of people. By serving as a natural interface to services ranging from home automation to media players, conversational assistants help people perform many tasks with ease, such as setting timers, playing music and managing to-do lists. While these systems offer useful capabilities, they are largely passive and unaware of the human behavioral context in which they are used. In this work, we explore how off-the-shelf conversational assistants can be enhanced with acoustic-based human activity recognition by leveraging the short interval after a voice command is given to the device. Since always-on audio recording can pose privacy concerns, our method is unique in that it does not require capturing and analyzing any audio other than the speech-based interactions between people and their conversational assistants. In particular, we leverage background environmental sounds present in these short duration voice-based interactions to recognize activities of daily living. We conducted a study with 14 participants in 3 different locations in their own homes. We showed that our method can recognize 19 different activities of daily living with average precision of 84.85% and average recall of 85.67% in a leave-one-participant-out performance evaluation with 30-second audio clips bound by the voice interactions.

This paper explores the methodological possibilities of listening to more-than-human sounds as an entry point to critical analysis. Through attending to the sound of a leafblower as it resonates across a university campus, this article draws lines between the resonances of the leafblower, higher education, and white supremacy to explore how sounds become embedded in bodies and spaces. In addition, this article offers a methodology of listening as a process of attunement that provokes readings beyond what is immediately heard, seen, or felt. To listen to the sound of the leafblower and what it does, how it resonates is to attune to how that sound works, how it operates in the production and discourses of place. In other words, this article wonders how listening, as a methodological practice, provokes critical questions about place and space, and how sound (and particularly nonhuman or more than human sounds) functions in qualitative methodology.

To assist an investigation process, forensic experts compare and analyze audio recordings. Speech utterances are compared by humans and/or machines for use in court for investigation. Scientific research community insists for specific automatic or human-based approach to identify uniquxy2e audio features from identical twins group. Filters can be employed to enhance an audio recording for improving clarity. This may entail removal of unnecessary noise to enrich the intelligibility of speech. Forensic audio experts can examine a variety of characteristics of the audio recording to decide the possibility of alterations in the collected evidences. This includes confirming the integrity and authenticating that the content is what it purports to be. Thiswork named as FIST(Forensic Investigation for Twin Identification from Speech: Perceptual and Gamma-tone Features and Models) proposes an automated system to identify a twin from identical twin pairs by the use of gamma-tone features and perceptual features.The proposed features are excerpted from the set of training speeches and templates are created for each twin based on vector quantisation (VQ), Fuzzy C means clustering (FCM) and multivariate hidden Markov modelling (MHMM) techniques. For testing, features are extracted from the set of test utterances and worked out to the templates for classification. Based on the type of classifier used, classification of twin is carried out with minimum distance and maximum loglikelihood value. The proposed features are examinedfor sub-optimal and true success rates as key performance metrics to assess the system and also a comparative analysis is made across the proposed features. Among the inspected features, Gammatone energy features expose better performance in comparison to perceptual features by attaining the overall sub-optimal success rate and true success rate as97.8375% and 92.75% for Gammatone energy features with VQ based modelling technique. This work FIST has also been analysed by inducing disturbance in the form of speech interference from their own twin pairs and Gamma-tone energy feature with VQ based modelling technique performs better for twin identification. A high claim of 99.625% and 95.0625% accuracy has been achieved by employing decision level fusion classifier.

In a leading article by Sir Percival Philips in the UK popular newspaper, the Daily Mail, July 16, 1928, came the following headlines: “Millions Lost by Noise – Cities’ Worst Plague – Menace to Nerves and Health – What is Being Done to Stop it”. The article was supported by research from Prof Henry J. Spooner, who had been researching and campaigning on the ill-effects of noise and its economic impact. The article sparked subsequent discussion and follow-up articles in the Daily Mail and its international partners. In an era of rapid technological change, that was on the cusp of implementing sound pressure measurements, the Daily Mail, in collaboration with the Columbia Graphophone Company Ltd, experimented with sound recording technology and commentary in the field to help communicate perceived loudness and identify the sources of “unnecessary noise”. This resulted in the making of series of environmental sound recordings from five locations across central London during September 1928, the findings of which were documented and discussed in the Daily Mail at the time, and two recordings commercially released by Columbia on shellac gramophone disc. This was probably the first concerted anti-noise campaign of this type and scale, requiring huge technological efforts. The regulatory bodies and politicians of the time reviewed and improved the policies around urban noise shortly after the presentation of the recordings, which were also broadcast from the BBC both nationally and internationally, and many members of the public congratulated and thanked the Daily Mail for such an initiative. Despite its unpreceded scale and impact, and the recent scholarly attention on the history of anti-noise campaigning, this paper charts and contextualises the Daily Mail’s London Street Noise campaign for the first time. As well as historical research, this data has also been used to start a longitudinal comparative study still underway, returning to make field recordings on the site on the 80th and 90th anniversaries and during the COVID-19 lockdown, and shared on the website londonstreetnoises.co.uk.

Background: In forensic science the process of proving authenticity of audio recording plays an important role. In recent times, Forensic experts mostly receives digital recording for authentication as compared to analog recording. A digitally altered audio signal, leaves no visual indications of being tampered, and it will be indistinguishable from an original audio signal. Objective: To highlight the significance of latency feature of mobile phone handsets in forensic science via comparing input audio latency feature of Samsung and Motorola mobile phone in two audio formats. Methods: In this work two wellestablished and most used brands of mobile phones were considered for comparison: SAMSUNG and MOTOROLA. In the present paper, the digital audio samples have been recorded using 20 mobile phones of various models from two different makes i.e. SAMSUNG and MOTOROLA, in two audio formats i.e. WAV and 3GP. Audio samples were then analysed using Adobe Audition 3.0 software for the input audio latency feature of mobile phones and compared. Findings: Input audio latency value of digital audio recordings can be helpful in forensic identification of make and model of source mobile phone. Novelty: A new technique in digital forensics, to classify the given audio samples on the basis of input audio latency feature and identifying the make of source mobile handsets. Keywords: Authentication; digital audio; forensic science; adobe audition; mobile phone

Jazz is the first type of music art the earliest stage of development of which had been recorded. A single play recorded in 1917 by the quintet Original Dixieland “Jass” Band from New Orleans is known in history as the first jazz record. There’s a perception in the academic community that the musical material on this record can hardly be considered as a typical representative of jazz music of that period. The music was performed by the white musicians, though most first jazz bands were black, and the music was far from a real solo improvisation. However, it was not typical in the first place because it had been recorded. The research subject of the article is the influence of sound recording technology on jazz culture at the stage of its foundation. In those years, if jazz musicians wanted to make a recording they had to bear in mind numerous peculiarities of sound recording technology. The author gives special attention to the analysis of the consequences of reproducibility of a recording for jazz musicians, and for the audience’s perception. As a research methodology, the author uses the comprehensive approach which includes the study of historical sources and jazz musicians’ memoirs related to the sound recording industry. The research proves that audio recordings are not sufficient as a source for critical research of the first jazz gramophone record, and suggests alternative approaches to its interpretation. &nbsp

Background The prediction violation account of automatic or pre-attentive change detection assumed that the inferior frontal cortex (IFC) is involved in establishing a prediction model for detecting unexpected changes. Evidence supporting the IFC’s contribution to prediction model is mainly based on the Mismatch Negativity (MMN) to deviants violating predictions that are established based on the frequently presented standard events. However, deviant detection involves processes, such as events comparison, other than prediction model establishment. Objective The current study investigated the critical role of the IFC in establishing a prediction model during standards processing for subsequent deviant detection. Methods Transcranial Magnetic Stimulation (TMS) was applied at the IFC to disrupt the processing of the initial 2 or 5 standards of a 3-, 6-, or 9-standard train, while the MMN responses to pitch deviant presented after the standard trains were recorded and compared. Results An abolishment of MMN was only observed when TMS was delivered to the IFC at the initial 2 standards of the 3-standard train, but not at the initial 5 standards, or when TMS at the vertex or TMS sound recording was applied. The MMNs were also preserved when IFC TMS, vertex TMS, or TMS sound recording was applied at the initial 2 or 5 standards of longer trains. Conclusion The IFC plays a critical role in processing the initial standards of a short standard train for subsequent deviant detection. This result is consistent with the prediction violation account that the IFC is important for establishing the prediction model.

This article argues for a shift toward aurality and away from the emphasis on orality that has long been a keynote in criticism about the work of Juan Rulfo. To attend to the ears that listen rather than solely the voice that speaks, I not only consider the Jaliscan writer's entire oeuvre but also turn to a seldom-studied yet readily available archive: Rulfo's recordings of a few stories from El llano en llamas and two fragments from Pedro Paramo. Addressing these audio versions amplifies the importance of the aural throughout Rulfo's writings and expands on the readings of other critics who examine some of the sounds that echo across his works but who rarely acknowledge the constitutive role of the listener. And just as Rulfo's own experiences with tape reveal these listening techniques, his representations of other sound reproduction technologies portray the effects of changing aural perceptions and practices

Recently, it has been discovered that the electric network frequency (ENF) could be captured by digital audio, video, or even image files, and could further be exploited in forensic investigations. However, the existence of the ENF in multimedia content is not a sure thing, and if the ENF is not present, ENF-based forensic analysis would become useless or even misleading. In this paper, we address the problem of ENF detection in digital audio recordings, which is modeled as the detection of a weak (ENF) signal contaminated by unknown colored wide-sense stationary (WSS) Gaussian noise, while the signal also contains multiple unknown random parameters. We first derive three Neyman-Pearson (NP) detectors, i.e., general matched filter (GMF), matched filter (MF)-like detector, and the asymptotic approximation of the GMF, and choose the MF-like detector as the clairvoyant detector. For practical detectors, we show that the generalized likelihood ratio test (GLRT) could not be efficiently obtained due to the unknown noise and large matrix inversion. Alternatively, we propose two least-squares (LS)-based time domain detectors termed as LS-likelihood ratio test (LRT) and naive-LRT. Further, we propose a time-frequency (TF) domain detector, termed as TF detector, which exploits the a priori knowledge of the ENF. The performances of the derived detectors are extensively analyzed in terms of test statistic distributions, threshold selection, and computational complexity. The naive-LRT detector is found to be only effective for very short recordings. As the data recording length increases, both LS-LRT and TF detectors yield effective detection results, while the latter is approximately a constant false alarm rate (CFAR) detector. Practical experiments using real audio recordings justify the effectiveness of the proposed detectors and our analysis.

The usage of drones is increasingly spreading into new fields of application, ranging from agriculture to security. One of these new applications is sound recording in areas of difficult access. The challenge that arises when using drones for this purpose is that the sound of the recorded sources must be separated from the noise produced by the drone. The intensity of the noise emitted by the drone depends on several factors such as engine power, propeller rotation speed, or propeller type. Noise reduction is thus one of the greatest challenges for the next generations of unmanned aerial vehicles (UAVs) and unmanned aerial systems (UAS). Even though some advances have been made on that matter, drones still produce a considerable noise. In this article, we approach the problem of removing drone noise from single-channel audio recordings using blind source separation (BSS) techniques, and in particular, the singular spectrum analysis algorithm (SSA). Furthermore, we propose an optimization of this algorithm with a spatial complexity of $\mathcal {O}(nt)$ , which is significantly lower than the naive implementation which has a spatial complexity of $O(tk^{2})$ (where $n$ is the number of sounds to be recovered, $t$ is the signal length and $k$ is the window size). The best value for each parameter (window length and number of components used to reconstruct the source) is selected by testing a wide range of values on different noise-sound ratios. Our system can greatly reduce the noise produced by the drone on said recordings. On average, after the recording has been processed by our method, the noise is reduced by 1.41 decibels.

With the popularity of mobile devices and the emergence of various audio-editing tools, it becomes easier to produce and forge audio files. Many criminals will forge false audio information as evidence. Therefore, audio forensics technology becomes particularly important. Audio recording device identification technology, which can verify the authenticity and uniqueness of the evidence obtained, is one of the promising branches of audio forensics technology. In this article, a novel neural-network-based framework using the device noise feature is proposed to identify the source of recording according to the device traces generated by the device during the recording. We also propose a new neural network model RARS (Recognition of Audio Recording Source based on residual neural network). The proposed framework achieves state-of-the-art performance on MOBIPHONE, the only publicly available dataset in this field. Moreover, we build a new dataset based on the latest mobile phones and tablet devices. Our method achieves good performance on both the two datasets, which proves that our model has a certain degree of reusability and robustness.

Identification of the acoustic environment from an audio recording, also known as acoustic scene classification, is an active area of research. In this paper, we study dynamically-changing background acoustic scenes from the egocentric perspective of an individual in a workplace. In a novel data collection setup, wearable sensors were deployed on individuals to collect audio signals within a built environment, while Bluetooth-based hubs continuously tracked the individual's location which represents the acoustic scene at a certain time. The data of this paper come from 170 hospital workers gathered continuously during work shifts for a 10 week period. In the first part of our study, we investigate temporal patterns in the egocentric sequence of acoustic scenes encountered by an employee, and the association of those patterns with factors such as job-role and daily routine of the individual. Motivated by evidence of multifaceted effects of ambient sounds on human psychology, we also analyze the association of the temporal dynamics of the perceived acoustic scenes with particular behavioral traits of the individual. Experiments reveal rich temporal patterns in the acoustic scenes experienced by the individuals during their work shifts, and a strong association of those patterns with various constructs related to job-roles and behavior of the employees. In the second part of our study, we employ deep learning models to predict the temporal sequence of acoustic scenes from the egocentric audio signal. We propose a two-stage framework where a recurrent neural network is trained on top of the latent acoustic representations learned by a segment-level neural network. The experimental results show the efficacy of the proposed system in predicting sequence of acoustic scenes, highlighting the existence of underlying temporal patterns in the acoustic scenes experienced in workplace.

This article troubles a tendency in literary criticism to equate novelistic speech with sound recording. It recovers the history of Joseph Faber's Euphonia (a speech simulator exhibited from the 1840s to the 1880s) in order to articulate an alternative vocal ontology of the novel—one of simulation rather than recording. The Euphonia has striking parallels to the eponymous heroine of George Du Maurier's Trilby (1894): their comparably mechanized utterances flatten hierarchies of difference, instead of phonographically using the voice to archive particularity. In dialogue, the Euphonia and Trilby elucidate the relationship between page and voice as always collaborative, though contoured by power.

This paper deals with a score–audio music retrieval task where the aim is to find relevant audio recordings of Western classical music, given a short monophonic musical theme in symbolic notation as a query. Strategies for comparing score and audio data are often based on a common mid-level representation, such as chroma features, which capture melodic and harmonic properties. Recent studies demonstrated the effectiveness of neural networks that learn task-specific mid-level representations. Usually, such supervised learning approaches require score–audio pairs where the score's individual note events are aligned to the corresponding time positions of the audio excerpt. However, in practice, it is tedious to generate such strongly aligned training pairs. As one contribution, we show how to apply the Connectionist Temporal Classification (CTC) loss in the training procedure, which only uses weakly aligned training pairs. In such a pair, only the time positions of the beginning and end of a theme occurrence are annotated in an audio recording, rather than requiring local alignment annotations. We evaluate the resulting features in our theme retrieval scenario and show that they improve the state of the art for this task. As a main result, we demonstrate that with the CTC-based training procedure using weakly annotated data, we can achieve results almost as good as with strongly annotated data. Furthermore, we assess our chroma features in depth by inspecting their temporal smoothness or granularity as an important property and by analyzing the impact of different degrees of musical complexity on the features.

The purpose of the article is to review, systematize and analyze the functional characteristics of the sound supply means of stage productions. The research methodology consists of the following approaches: system-historical (to study the problem), art history (to clarify the role of the sound system in modern stage practice), structural-analytical (for the functional classification of the components of the stage sound system). Scientific novelty. In the offered research the modern sound maintenance system of theatrical and entertaining productions is considered, its basic constituent elements have been systematized and analyzed; the role of technical means in work of the sound director on sound imagery creation of production has been comprehended. Conclusions. The study found that the profession of theater sound director and entertainment productions involves, in addition to sound recording skills, selection, editing and musical montage, noise, voice and other types of sound effects in accordance with the director’s design, and the ability to work with analog and digital sound equipment. It has been established that the main elements of the stage sound equipment system include microphones, monitors, amplifiers, speakers and mixing consoles. For example, during a rock concert on stage, musicians and vocalists use different types of microphones, place combo amplifiers of their electric instruments next to musicians; monitors on the floor in front of them invisible audiences shoot from the side of the stage or hang over the portal arch mirror the stage and directed towards the listeners are portals. In the center of the auditorium is a sound engineer’s console. It has been proved that an important component of the system of quality sound design is the room’s acoustic characteristics, which must be taken into account and improved during the events organization. It has been found that with the help of modern wireless sound systems it is possible to create conditions for theatrical and entertainment events without restrictions on their acoustic characteristics.

This article does not present an in-depth overview but is meant to serve as an introduction to the newcomers to this field of acoustics. A brief explanation is given for different sound reproduction formats (Ambisonics and binaural), together with some of the standards, and listening test tools used in the design of listening tests. Primarily the listening tests in the field of subjective evaluation of sound insulation and acoustic comfort have been discussed.

Indonesia is a biodiversity country and has much of samples of bioacoustics but there are no bioacoustics data collected and saved to be referred. Bioacoustics is a study of frequency range, sound amplitudo intensity, sound fluctuation, and sound patterns. It is very useful to study more about population presumption and species determination. This insect bioacoustics research is done at Gunung Gede Pangrango National Park and aims to analyse variety of sound frequency of cicada and cricket. Methods which are used are recording the sounds, editing and analyzing the record result with Praat and Raven Lite 2.0 softwares, and analysing the environment. Analysing the sounds which is done is to find miximum frequency, minimum frequency, and average frequency. The result of the sounds analysis is compared to database in Singing Insect of North America (SINA). Environmental analysing includes temperature, air humidity, and light intensity. There are nine cicada sound recording files and twenty four cricket sound recording files. Cicada has high sound characteristic (9,168.2 Hz) and cricket has low sound characteristic (3,311.80 Hz). Comparation to Singing Insect of North America (SINA) database shows that the cicada’s sound is resemble to Tibicen marginalis and the cricket’s sound is resemble to Grylodes sigillatus.

The problems of correlation of the principles of civil procedural law with the prohibition of audio recording in a closed court session are considered. The problematics of the democracy of the civil procedure is disclosed when the case is considered in a closed court session, a number of guarantees are proposed, taking into account the legislative prohibition on audio recording of a closed court session by persons participating in the case.