Digital Audio Files

2014 ◽  
pp. 386-397
Keyword(s):  
Digital Audio ◽  
Audio Files

scholarly journals Self-Practice of Stabilizing and Guided Imagery Techniques for Traumatized Refugees via Digital Audio Files: Qualitative Study

10.2196/17906 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e17906
Author(s):  
Catharina Zehetmair ◽  
Ede Nagy ◽  
Carla Leetz ◽  
Anna Cranz ◽  
David Kindermann ◽  
...  
Keyword(s):  
Guided Imagery ◽  
Mental Health Problems ◽  
The Self ◽  
Digital Audio ◽  
Safe Place ◽  
Time Space ◽  
Increased Risk ◽  
Audio Files ◽  
Imagery Techniques

Background Refugees have an increased risk of developing mental health problems. There are insufficient psychosocial care structures to meet the resulting need for support. Stabilizing and guided imagery techniques have shown promising results in increasing traumatized refugees’ emotional stabilization. If delivered via audio files, the techniques can be practiced autonomously and independent of time, space, and human resources or stable treatment settings. Objective This study aimed to evaluate the self-practice of stabilizing and guided imagery techniques via digital audio files for traumatized refugees living in a reception and registration center in Germany. Methods From May 2018 to February 2019, 42 traumatized refugees participated in our study. At T1, patients received digital audio files in English, French, Arabic, Farsi, Turkish, or Serbian for self-practice. Nine days later, at T2, a face-to-face interview was conducted. Two months after T2, a follow-up interview took place via telephone. Results At T2, about half of the patients reported the daily practice of stabilizing and guided imagery techniques. At follow-up, the average frequency of practice was once weekly or more for those experiencing worse symptoms. No technical difficulties were reported. According to T2 and follow-up statements, the techniques helped the patients dealing with arousal, concentration, sleep, mood, thoughts, empowerment, and tension. The guided imagery technique “The Inner Safe Place” was the most popular. Self-practice was impeded by postmigratory distress factors, like overcrowded accommodations. Conclusions The results show that self-practice of stabilizing and guided imagery techniques via digital audio files was helpful to and well accepted by the assessed refugees. Even though postmigratory distress factors hampered self-practice, “The Inner Safe Place” technique was particularly well received. Overall, the self-practiced audio-based stabilizing and guided imagery techniques showed promising results among the highly vulnerable group of newly arrived traumatized refugees.

Architectures of Existing and Conceptual Applications of Podcasting in E-learning Systems

2008 ◽  
pp. 80-97
Author(s):  
Stephen R. Chastain ◽  
Jason Caudill
Keyword(s):  
Mobile Learning ◽  
Low Cost ◽  
Ease Of Use ◽  
Learning Systems ◽  
Digital Audio ◽  
Instructional Tool ◽  
E Learning ◽  
User Access ◽  
Audio Files ◽  
And Training

Podcasting has quickly emerged as a leading technology in the new field of mobile learning. Tracing this new technology’s history over the past two years reveals just how broadly the use of digital audio files may become in the fields of education and training. The ease of use, low cost of creation and hosting, and most importantly pervasiveness of user access to compatible hardware combine to make podcasting a major force in both traditional and distance education. This chapter explores the history, technology, and application of podcasting as an instructional tool.

Creative Ideas for Biology Podcasts: The Immune System as an Example

2011 ◽  
Vol 73 (3) ◽  
pp. 171-175 ◽  
Author(s):  
Janet De Souza-Hart
Keyword(s):  
Immune Response ◽  
Immune System ◽  
Conceptual Understanding ◽  
Digital Audio ◽  
Lord Of The Rings ◽  
Course Material ◽  
Human Immune Response ◽  
Human Immune ◽  
Audio Files ◽  
The Many

Podcasts (digital audio files) can be utilized creatively to supplement classroom learning. They can be both easily created by instructors and conveniently accessed by students. Students are very receptive to the use of this type of technology as a way to reinforce conceptual understanding of course material. An activity combining a podcast with an active-learning worksheet references the literary classic "The Lord of the Rings" as an analogy to help students understand the many proteins, cells, and processes involved in the human immune response. This activity has helped a significant number of students improve their understanding of this subject.

scholarly journals Environment Recognition for Digital Audio Forensics Using MPEG-7 and MEL Cepstral Features

2011 ◽  
Vol 62 (4) ◽  
pp. 199-205 ◽  
Author(s):  
Ghulam Muhammad ◽  
Khalid Alghathbar
Keyword(s):  
Recognition Accuracy ◽  
Digital Audio ◽  
Mel Frequency Cepstral Coefficients ◽  
Environmental Sound ◽  
Area Of Interest ◽  
Audio Features ◽  
Audio Forensics ◽  
Cepstral Features ◽  
Environment Recognition ◽  
Audio Files

Environment Recognition for Digital Audio Forensics Using MPEG-7 and MEL Cepstral FeaturesEnvironment recognition from digital audio for forensics application is a growing area of interest. However, compared to other branches of audio forensics, it is a less researched one. Especially less attention has been given to detect environment from files where foreground speech is present, which is a forensics scenario. In this paper, we perform several experiments focusing on the problems of environment recognition from audio particularly for forensics application. Experimental results show that the task is easier when audio files contain only environmental sound than when they contain both foreground speech and background environment. We propose a full set of MPEG-7 audio features combined with mel frequency cepstral coefficients (MFCCs) to improve the accuracy. In the experiments, the proposed approach significantly increases the recognition accuracy of environment sound even in the presence of high amount of foreground human speech.

scholarly journals Klasifikasi Lagu Berdasarkan Genre pada Format WAV

2014 ◽  
Vol 10 (1) ◽  
pp. 145
Author(s):  
Nurmiyati Tamatjita ◽  
Agus Harjoko
Keyword(s):  
Digital Media ◽  
Hip Hop ◽  
Euclidean Distance ◽  
Average Energy ◽  
Digital Audio ◽  
Zero Crossing ◽  
Music Genres ◽  
Zero Crossing Rate ◽  
Audio Files

AbstrakDalam dunia yang berkembang pesat, media audio semakin komplek. Karena itulah diperlukan sebuah mekanisme penentuan jenis lagu (genre) yang tepat secara efektif dan efisien.  Pencarian secara manual sudah tidak efektif dan efisien lagi karena banyaknya data yang tersimpan.          Zero Crossing Rate (ZCR), Average Energy (E) dan Silent Ratio (SR) adalah 3 Feature Extraction yang digunakan untuk klasifikasi pencarian 12 genre.Tiga dimensi adalah bentuk visualisasi pengukuran tingkat kemiripan sebuah data berdasarkan hasil klasifikasi yang diinput oleh user.            Dalam penelitian ini pengujian klasifikasi menggunakan metode 3, 6, 9 dan 12 genre melalui jarak terdekat (Euclidean Distance). Hasil pengujian yaitu menunjukkan bahwa 3 genre yaitu Balada, Blues dan Classic menunjukkan = 96,67%, 6 genre yaitu Balada, Blues, Classic, Harmony, Hip Jop dan Jazz menunjukkan = 70% dan 9 genre yaitu Balada, Blues, Classic, Harmony, Hip Hop, Jazz, Keroncong, Latin dan Pop menunjukkan = 53,33% serta 12 genre = 33,33% Kata Kunci— Zero Crossing Rate (ZCR), Average Energy (E), Silent Ratio (SR), Euclidean Distance  Abstract            Music genre is getting complex from time to time. As the size of digital media grows along with amount of data, manual search of digital audio files according to its genre is considered impractical and inefficient; therefore a classification mechanism is needed to improve searching.            Zero Crossing Rate (ZCR), Average Energy (E) and Silent Ratio (SR) are a few of features that can be extracted from digital audio files to classify its genre. This research conducted to classify digital audio (songs) into 12 genres: Ballad, Blues, Classic, Harmony, Hip Hop, Jazz, Keroncong, Latin, Pop, Electronic, Reggae and Rock using above mentioned features, extracted from WAV audio files. Classification is performed several times using selected 3, 6, 9 and 12 genres respectively.            The result shows that classification of 3 music genres (Ballad, Blues, Classic) has the highest accuracy (96.67%), followed by 6 genres (Ballad, Blues, Classic, Harmony, Hip Hop, Jazz) with 70%, and 9 genres (Ballad, Blues, Classic, Harmony, Hip Hop, Jazz, Keroncong, Latin, Pop) with 53.33% accuracy. Classification of all 12 music genres yields the lowest accuracy of 33.33%.   Keywords— Zero Crossing Rate (ZCR), Average Energy (E), Silent Ratio (SR), Euclidean Distance

scholarly journals Deep Convolutional Neural Network based Image Steganogrpahy Technique for Audio-Image Hiding Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 2187-2189
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Digital Image ◽  
Digital Audio ◽  
Least Significant Bit ◽  
Stego Image ◽  
Vast Number ◽  
Learning Techniques ◽  
Network Concept ◽  
Audio Files

Steganography is one expanding filed in the area of Data Security. Steganography has attractive number of application from a vast number of researchers. The most existing technique in steganogarphy is Least Significant Bit (LSB) encoding. Now a day there has been so many new approaches employing with different techniques like deep learning. Those techniques are used to address the problems of steganography. Now a day’s many of the exisiting algorithms are based on the image to data, image to image steganography. In this paper we hide secret audio into the digital image with the help of deep learning techniques. We use a joint deep neural network concept it consist of two sub models. The first model is responsible for hiding digital audio into a digital image. The second model is responsible for returning a digital audio from the stego image. Various vast experiments are conducted with a set of 24K images and also for various sizes of images. From the experiments it can be seen proposed method is performing more effective than the existing methods. The proposed method also concentrates the integrity of the digital image and audio files.

Map-Based User Interfaces for Music Information Retrieval

2009 ◽  
pp. 321-329
Author(s):  
Robert Neumayer ◽  
Andreas Rauber
Keyword(s):  
Mobile Devices ◽  
User Interfaces ◽  
Digital Audio ◽  
Digital Collections ◽  
Desktop Computers ◽  
Unsupervised Neural Network ◽  
Audio Files ◽  
Self Organising Map ◽  
Music Information ◽  
Alternative Interfaces

In this chapter, we introduce alternative ways to access digital audio collections. We give an overview of existing applications based on tow-dimensional, map-like representations of music collections. Further, we explain two applications for accessing audio files that are based on the Self-Organising Map, an unsupervised neural network model. These two applications—PlaySOM and PocketSOM—will be explained in greater detail, paying special attention to their unique properties and implementations for several mobile devices. These examples are supposed to gain the readers’ interest for alternative interfaces to large audio collections. Besides, we hope to show that alternative interfaces are feasible for both desktop computers and mobile devices and offer a practical approach to pressing issues in accessing digital collections.

Methods of Time-Frequency Analysis in Authentication of Digital Audio Recordings

2010 ◽  
Vol 56 (3) ◽  
pp. 257-262 ◽  
Author(s):  
Rafał Korycki
Keyword(s):  
Frequency Analysis ◽  
Visual Inspection ◽  
Frequency Measurement ◽  
Digital Audio ◽  
Time Frequency Analysis ◽  
Electric Network ◽  
Time Frequency ◽  
Audio Recordings ◽  
Frequency Criterion ◽  
Audio Files

Methods of Time-Frequency Analysis in Authentication of Digital Audio RecordingsThis paper describes the problem of tampering detection and discusses the main methods used for authenticity analysis of digital audio recordings. For the first topic, two frequency measurement algorithms based on electric network frequency criterion are applied. Time-frequency analysis is used and improved with reassignment method for purpose of visual inspection of modified recordings. The algorithms are shortly described and exemplary plots are presented with interpretation. The last described method, recently proposed, is based on checking frame offsets in compressed audio files.

Detection of Montage in Lossy Compressed Digital Audio Recordings

2015 ◽  
Vol 39 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Rafał Korycki
Keyword(s):  
Audio Coding ◽  
Digital Audio ◽  
Tampering Detection ◽  
Detection Algorithms ◽  
Perceptual Audio Coding ◽  
Audio Recordings ◽  
Spectral Coefficients ◽  
Previous Algorithm ◽  
Audio Files ◽  
Music Database

Abstract This paper addresses the problem of tampering detection and discusses methods used for authenticity analysis of digital audio recordings. Presented approach is based on frame offset measurement in audio files compressed and decoded by using perceptual audio coding algorithms which employ modified discrete cosine transform. The minimum values of total number of active MDCT coefficients occur for frame shifts equal to multiplications of applied window length. Any modification of audio file, including cutting off or pasting a part of audio recording causes a disturbance within this regularity. In this study the algorithm based on checking frame offset previously described in the literature is expanded by using each of four types of analysis windows commonly applied in the majority of MDCT based encoders. To enhance the robustness of the method additional histogram analysis is performed by detecting the presence of small value spectral components. Moreover, computation of maximum values of nonzero spectral coefficients is employed, which creates a gating function for the results obtained based on previous algorithm. This solution radically minimizes a number of false detections of forgeries. The influence of compression algorithms' parameters on detection of forgeries is presented by applying AAC and Ogg Vorbis encoders as examples. The effectiveness of tampering detection algorithms proposed in this paper is tested on a predefined music database and compared graphically using ROC-like curves.

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