Audio Editing Research Articles

Use of music software in professional activity of music teacher

The article defines the possibilities of using of information and communication technologies in professional activity of music teachers. It is determined the ways of practical application of music software, including audio editors, virtual studios, auto arrangement software and scorewriters. It is investigated the features of modern software products that can be used in professional activity of music teachers

Teaching about mechanical waves and sound with a tuning fork and the Sun

Literature in Physics Education has shown that students encounter many difficulties in understanding wave propagation. Such difficulties lead to misconceptions also in understanding sound, often used as context to teach wave propagation. To address these issues, we present in this paper a module in which the students are engaged in computer-based activities dealing with sounds produced by a tuning fork and the Sun. The main reason underlying such choice is to show how the same measurement technique (spectral analysis) can be used to obtain information about very different phenomena. The activities build on a formal analogy to determine the fundamental frequency of sounds emitted by the two sources (tuning fork and Sun). Using a digital audio editor, the sounds are analyzed using three types of graphs: intensity versus time (waveform), intensity versus frequency (spectrum), and frequency versus time (spectrogram). The aim of the activities is to address students’ alternative conceptions about the frequency and propagation of mechanical waves using a multi-representation of the same phenomenon. Examples of frequency measurements for the analyzed sounds are reported, as well as paper-and-pencil tasks to determine velocity of sound in the two phenomena. Implications for the teaching of waves and sound are finally discussed.

Verification of hidden speaker behind transformation disguised voices

Voice transformation, which has been integrated in many audio (speech) processing tools, is a common operation to change a person's voice and to conceal his or her identity. It can deceive human beings and automatic speaker verification (ASV) systems easily, and thus it presents threats to security. Until now, few efforts have been reported on the recognition of hidden speakers from such disguised voices. In this paper, we propose concrete countermeasures to erase the disguise effects and verify the speaker's identity from voice transformation disguised voices. The proposed system is tested by commonly used audio editors and voice transformation algorithms. The experimental results show that the performances of baseline ASV system without our proposed countermeasures are entirely destroyed by voice transformation disguise with equal error rates (EERs) higher than 40%; while with our proposed countermeasures, the verification performances are improved significantly with EERs lowered to 3%–4%.

Time of flight measurement of speed of sound in air with a computer sound card

A computer sound card and freely available audio editing software are used to measure accurately the speed of sound in air using the time-of-flight method. In addition to speed of sound measurement, inversion behaviour upon reflection from an open and closed end of a pipe is demonstrated. Also, it is demonstrated that the reflection at an open end of a pipe occurs slightly outside the pipe. The equipment needed is readily available to any student with access to a microphone, loudspeaker and computer.

Audio authenticity: Duplicated audio segment detection in waveform audio file

Waveform audio (WAV) file is a widely used file format of uncompressed audio. With the rapid development of digital media technology, one can easily insert duplicated segments with powerful audio editing software, e.g. inserting a segment of audio with negative meaning into the existing audio file. The duplicated segments can change the meaning of the audio file totally. So for a WAV file to be used as evidence in legal proceedings and historical documents, it is very importance to identify if there are any duplicated segments in it. This paper proposes a method to detect duplicated segments in a WAV file. Our method is based on the similarity calculation between two different segments. Duplicated segments are prone to having similar audio waveform, i.e., a high similarity. We use fast convolution algorithm to calculate the similarity, which makes our method quit efficient. We calculate the similarity between any two different segments in a digital audio file and use the similarity to judge which segments are duplicated. Experimental results show the feasibility and efficiency of our method on detecting duplicated audio segments.

Acoustics labs for a general education math and music course

This paper describes audio demonstrations and experiments that I use in my university level, general education mathematics course “Sounding Number: Music and Mathematics from Ancient to Modern Times.” These particular experiments illustrate frequency, timbre, pitch, beats, spectra, dissonance, tuning, and scale construction, which are a subset of the topics covered in the class. They can be performed with the free, open-source audio editor and recorder Audacity®.

Direct measurement of the speed of sound using a microphone and a speaker

We present a simple and accurate experiment to obtain the speed of sound in air using a conventional speaker and a microphone connected to a computer. A free open source digital audio editor and recording computer software application allows determination of the time-of-flight of the wave for different distances, from which the speed of sound is calculated. The result is in very good agreement with the reported value in the literature.

음원을 이용한 멀티미디어 휴대용 단말장치 판별

다양한 오디오 편집 기술이 개발됨으로써 오디오 데이터의 변경이 보다 쉬워지고 그 결과로 위변조 같은 다양한 사회 문제가 발생하고 있다. 현재 이런 문제를 해결하기 위해 디지털 포렌식 기술이 활발히 연구되어지고 있다. 본 논문에서는 이러한 디지털 포렌식 기술 중의 하나로 모바일 기기를 판별하는 방법을 제안하였다. 제안 방법에서는 사람에게는 들리지 않지만 기기의 디자인과 IC로부터 발생하는 노이즈 특징을 이용한다. 위너필터를 사용하여 기기의 노이즈 음을 추출하고 MIRtoolbox를 이용하여 특징들을 추출한 후 이를 다층 신경망에 학습시켜 기기를 판별한다. 총 6개의 모바일 기기를 사용하였으며 5-fold test를 통하여 99.9%의 판별 성능을 보였다. 또한 UCC 사이트에 업로드 된 데이터에서도 노이즈 음을 통한 판별이 가능한지 실험을 진행하였으며 99.8%의 판별 성능을 보였다. Thanks to the development of diverse audio editing Technology, audio file can be easily revised. As a result, diverse social problems like forgery may be caused. Digital forensic technology is actively studied to solve these problems. In this paper, a hand-held device identification method, an area of digital forensic technology is proposed. It uses the noise features of devices caused by the design and the integrated circuit of each device but cannot be identified by the audience. Wiener filter is used to get the noise sounds of devices and their acoustic features are extracted via MIRtoolbox and then they are trained by multi-layer neural network. To evaluate the proposed method, we use 5-fold cross-validation for the recorded data collected from 6 mobile devices. The experiments show the performance 99.9%. We also perform some experiments to observe the noise features of mobile devices are still useful after the data are uploaded to UCC. The experiments show the performance of 99.8% for UCC data.

Automatic Music Stretching Resistance Classification Using Audio Features and Genres

Music stretching resistance (MSR) is a fresh but important concept in audio signal processing, which characterizes the ability of a music piece to be stretched in time (compressed or elongated) without objectionable perceptual artifacts. It has the potential to be highly demanded in various multimedia applications like music resizing, audio editing and multimedia integration, but there is almost no prior knowledge about this property of music in literature. In this letter, the task of MSR is formulated for the first time, and an MSR classification method that employs metric learning on audio features and genres is also proposed. It attempts to automate what human acceptable time-stretching rate range of music should be. The proposed method outperforms the reference classification methods in accuracy in the comparative experiments.

Open Source and Free E-Learning Tools Useful in LIS Education

E-learning is commonly referred to the intentional use of networked information and communications technology in teaching and learning. The present paper discusses the synchronous and asynchronous mode of e learning with its features. It also defines and summarizes the impact of open source software on teaching and learning process. The numerous open source e learning tools are discussed with examples such as Open source LMS, Open source authoring tools, Open source audio editing software, Open source social bookmarking tools, Open source CMS etc. It also throws light on free e learning tools useful in e learning such as Slideshare, Youtube, Wikis, RSS, Wordpress etc. The paper concludes with e learning initiatives in India.

Audio Watermarking by Coefficient Quantization in the DWT-DCT Dual Domain

Unauthorized copying and distribution of digital audio has been greatly facilitated by the wide availability of low-cost personal computers, portable devices, network access, and audio recording and editing software. One possible solution for copyright protection is audio watermarking. In this paper, we propose an effective and robust audio watermarking algorithm that employs both the discrete wavelet transform and the discrete cosine transform. The algorithm involves, first, pre-processing of the binary watermark image and then embedding it into the original audio by quantization of coefficients. Experiments on audio recordings of many different music styles confirm the robustness of the algorithm against a wide range of Stirmark attacks such as noise addition, compression, and filtering, as well as other common attacks.

Oral History in the Gender and Communication Course

CourseGender and CommunicationObjectivesThe Oral History assignment is a semester-long project. Students conduct oral history interviews relating to gender and communication. After completing the in-depth interview and creating an edited version for public presentation, students gain the following:Improved interviewing and listening (gained from conducting the interview itself).Practice using audio and/or visual editing equipment such as Audacity and iMovie or similar applications (gained from preparing an edited public presentation of the interview).The ability to appreciate and articulate the value of personal stories in making sense of complex social topics such as gender (gained from both listening to a person's in-depth stories about gender and preparing a final edited version of the interview).

Learner-Created Podcasts

This article describes uses for podcasts in music education, focusing on learner-created podcasts as an opportunity for students to construct and represent knowledge. The author outlines a podcast assignment that enables secondary and postsecondary students to examine and more deeply understand the meaning music holds for them and the role it has played in their lives. Using audio editing technology, students describe significant music experiences and combine spoken-word narration with illustrative music excerpts to create an audio documentary. Student benefits of engaging in the podcast creation process (e.g., opportunities for active music listening, enhanced reflection, self-expression, enriched communication, increased self-knowledge, and creativity) are addressed in the conclusion.

COMPETENCIAS DIGITALES DEL PROFESORADO Y ALUMNADO EN EL DESARROLLO DE LA DOCENCIA VIRTUAL. EL CASO DE LA UNIVERSIDAD DE LA LAGUNA

En este artículo se ofrecen algunos resultados de un estudio empírico desarrollado en la Universidad de La Laguna (España) con la finalidad de conocer los usos que el alumnado y el profesorado universitario hace de las TIC e indagar acerca de su influencia en los procesos de enseñanza y aprendizaje virtual en la educación superior. Para el desarrollo de este estudio se crearon dos cuestionarios independientes en el que participaron un total de 1561 estudiantes y 206 profesores. En el presente documento se aborda solo una parte de este estudio centrándose específicamente en la dimensión de uso de las TIC o competencia digital de profesores y estudiantes, donde se recoge información sobre actividades de búsqueda de información; desarrollo de procesos comunicacionales (consultar el correo electrónico, participar en foros, mensajería instantánea, usar redes sociales); elaboración de tareas (usar distintos paquetes ofimáticos, manejar programas de retoque de imágenes, utilizar programas de manipulación de audio y vídeo); actividades de ocio (descargar música y películas); actividades formativas (utilizar espacios de trabajo colaborativo, acceder a las aulas virtuales); actividades de participación en la web (editar páginas web personal, gestionar y dinamizar otras páginas web, escribir en blogs).

Scalable Music: Automatic Music Retargeting and Synthesis

AbstractIn this paper we propose a method for dynamic rescaling of music, inspired by recent works on image retargeting, video reshuffling and character animation in the computer graphics community. Given the desired target length of a piece of music and optional additional constraints such as position and importance of certain parts, we build on concepts from seam carving, video textures and motion graphs and extend them to allow for a global optimization of jumps in an audio signal. Based on an automatic feature extraction and spectral clustering for segmentation, we employ length‐constrained least‐costly path search via dynamic programming to synthesize a novel piece of music that best fulfills all desired constraints, with imperceptible transitions between reshuffled parts. We show various applications of music retargeting such as part removal, decreasing or increasing music duration, and in particular consistent joint video and audio editing.

Understanding Patient–Provider Conversations: What Are We Talking About?

Effective patient-provider communication is a critical aspect of the delivery of high-quality patient care; however, research regarding the conversational dynamics of an overall emergency department (ED) visit remains unexplored. Identifying both patterns and relative frequency of utterances within these interactions will help guide future efforts to improve the communication between patients and providers within the ED setting. The objective of this study was to analyze complete audio recordings of ED visits to characterize these conversations and to determine the proportion of the conversation spent on different functional categories of communication. Patients at an urban academic ED with four diagnoses (ankle sprain, back pain, head injury, and laceration) were recruited to have their ED visits audio recorded from the time of room placement until discharge. Patients were excluded if they were age < 18 years, were non-English-speaking, had significant history of psychiatric disease or cognitive impairment, or were medically unstable. Audio editing was performed to remove all silent downtime and non-patient-provider conversations. Audiotapes were analyzed using the Roter Interaction Analysis System (RIAS). RIAS is the most widely used medical interaction analysis system; coders assign each "utterance" (or complete thought) spoken by the patient or provider to one of 41 mutually exclusive and exhaustive categories. Descriptive statistics were calculated for all 41 categories and then grouped according to RIAS standards for "functional groupings." The percentage of total utterances in each functional grouping is reported. Twenty-six audio recordings were analyzed. Patient participants had a mean (±SD) age of 38.8 (±16.0) years, and 30.8% were male. Intercoder reliability was good, with mean intercoder correlations of 0.76 and 0.67 for all categories of provider and patient talk, respectively. Providers accounted for the majority of the conversation in the tapes (median = 239 utterances, interquartile range [IQR] = 168 to 308) compared to patients (median = 145 utterances, IQR = 80 to 198). Providers' utterances focused most on patient education and counseling (34%), followed by patient facilitation and activation (e.g., orienting the patient to the next steps in the ED or asking if the patient understood; 30%). Approximately 15% of the provider talk was spent on data gathering, with the majority (86%) focusing on biomedical topics rather than psychosocial topics (14%). Building a relationship with the patient (e.g., social talk, jokes/laughter, showing approval, or empathetic statements) constituted 22% of providers' talk. Patients' conversation was mainly focused in two areas: information giving (47% of patient utterances: 83% biomedical, 17% psychosocial) and building a relationship (45% of patient utterances). Only 5% of patients' utterances were devoted to question asking. Patient-centeredness scores were low. In this sample, both providers and patients spent a significant portion of their talk time providing information to one another, as might be expected in the fast-paced ED setting. Less expected was the result that a large percentage of both provider and patient utterances focused on relationship building, despite the lack of traditional, longitudinal provider-patient relationships.

Vocal Removal From Multiobject Audio Using Harmonic Information for Karaoke Service

Interactive audio services (IASs) usually provide users with audio editing functionality and they can render their own sounds according to their preference. For IASs, the spatial audio object coding (SAOC) is an appropriate multichannel coding tool that satisfies most of the required functionalities with relatively low bit rate. Nevertheless, the SAOC usually fails to remove a specific object successfully, especially the vocal object in the case of the Karaoke service. In addition, to expand the service to mobile environments, lower bit rate and complexity are required. Thus, we propose a new SAOC vocal harmonic coding technique to improve the background music quality in the Karaoke service. Namely, utilizing the harmonic information of the vocal object, we removed the harmonics of the vocal object remaining in the background music. Our experimental results confirm that the background music quality is improved by the proposed algorithm even with the low bit rate and complexity.

Cognitive Constructivist Theory of Multimedia: Designing Teacher-Made Interactive Digital

This paper discusses how educators could use the cognitive constructivist theory of multimedia (CCTM) to design interactive digital learning materials using Camtasia and Audacity. Camtasia allows educators to create videos that motivate students, inform parents and enhance learning. It allows educators to record live presentations or lectures and provide students with a file to review. Audacity is a free cross-platform audio editor and recorder for Windows, Mac OS X, GNU/Linux and other operating systems. CCTM advocates for the design of instruction using pictures, videos, audios and words that tap into the prior experiences of the learner, promote active learning, collaboration, personal autonomy, personal growth and alternative assessment that is aligned with multiple intelligences of learners as espoused by Gardener (1993) which are Linguistics, Logico-mathematics, Spatial, Musical, Bodily-kinesthetic, Interpersonal, Intrapersonal and Naturalist. Camtasia and Audacity promote use of CCTM because of their capabilities to construct knowledge through words, pictures, animations, videos and audio. Case studies show that use of teacher-made files could significantly impact students’ learning. Use of teacher-made interactive digital learning materials could revolutionize educational presentations and enhance e-learning delivery. CCMT produced by dynamic presentations creates a balance between the learners’ prior verbal and visual experiences, sensory repository, multiple intelligences and learning styles to construct new knowledge.

The nature and perception of human musical rhythms

Although human musical performances represent one of the most valuable achievements of mankind, the best musicians perform imperfectly. Musical rhythms are not entirely accurate and thus inevitably deviate from the ideal beat pattern. Nevertheless, computer generated perfect beat patterns are frequently devalued by listeners due to a perceived lack of human touch. Professional audio editing software therefore offers a humanizing feature which artificially generates rhythmic fluctuations. However, the built-in humanizing units are essentially random number generators producing only simple uncorrelated fluctuations. Here, for the first time, we establish long-range fluctuations as an inevitable natural companion of both simple and complex human rhythmic performances [1,2]. Moreover, we demonstrate that listeners strongly prefer long-range correlated fluctuations in musical rhythms. Thus, the favorable fluctuation type for humanizing interbeat intervals coincides with the one generically inherent in human musical performances. [1] HH et al., PLoS ONE,6,e26457 (2011). [2] Physics Today, invited article, submitted (2012).

Tempo Induction from Music Recordings Using Ensemble Empirical Mode Decomposition Analysis

Tempo and beat are among the most important features of Western music. Owing to the perceptual nature of tempo, its automatic analysis and extraction remains a difficult task for a large variety of music genres. Western music notation represents musical events using a hierarchical metrical structure distinguishing different time scales. This hierarchy is often modeled using three levels: the tatum, the tactus, and the measure. The tatum represents the shortest durational value in music that is not just an accidental phenomenon (Bilmes 1993). The tactus period is the most perceptually prominent period, and is the period at which most humans would tap their feet in time with the music (Lerdahl and Jackendoff 1983). The measure period is often related to the rate of harmonic change or the length of a repeated rhythmic pattern. This article deals with the estimation of the tempo at the tactus level. The tempo, which is the inverse of the tactus (beat) period, is expressed as the number of beats per minute (BPM). Tempo information is very important in many music information retrieval applications. Successful audio applications and music-analysis systems, such as video and audio editing software, cut-and-paste disk jockey applications, electronic instrument control, and synchronization, must be capable of analyzing and efficiently manipulating the rhythmic content of music. A review of different state-of-the art algorithms for tempo extraction from audio data is presented in the next section.