System and Method for Automatically Producing Haptic Events from a Digital Audio File

2012 ◽  
Vol 131 (2) ◽  
pp. 1676
Author(s):  
Christopher J. Ullrich
Keyword(s):  
Digital Audio ◽  
Audio File

scholarly journals STEGANOGRAFI AUDIO (WAV) MENGGUNAKAN METODE LSB (LEAST SIGNIFICANT BIT)

CCIT Journal ◽  
2016 ◽  
Vol 9 (2) ◽  
pp. 214-224
Author(s):  
Sugeng Santoso ◽  
Arisman Arisman ◽  
Windy Sentanu
Keyword(s):  
Digital Media ◽  
Digital Audio ◽  
Least Significant Bit ◽  
Audio File ◽  
Distributed Information ◽  
Hide Information

Security of distributed information is essential for maintaining the confidentiality of the information. The process of securing is done by hiding the information on other digital media that are not visible existence. This technique is called steganography, the art of hiding data into digital media with a particular method so that other people do not realize there is something in the digital media. In this paper conducted a study to hide information into digital audio file is not compressed (. Wav) as a carrier file using the Least Significant Bit Modification. Least Significant Bit Modification is a method of hiding information by modifying the last bits of carrier files with the bits of information and only cause changes in the value of a bit higher or a lower one. The system was designed with two main processes, namely phase Embedding and Extracting stage

scholarly journals A flexible method to create wave file features

2021 ◽  
Vol 11 (2) ◽  
pp. 1311
Author(s):  
Ghazi M. J. Qaryouti
Keyword(s):  
Audio Signal ◽  
Digital Audio ◽  
Human Knowledge ◽  
Signal Identification ◽  
Important Data ◽  
Recognition Time ◽  
Audio File ◽  
Voice Identification ◽  
Small Set ◽  
The Voice

Digital audio signal is one of the most important data type at present, it is used in various vital applications, such as human knowledge, security and banking applications, most applications require signal identification and recognition, and to increase the efficiency of these applications we must seek a method to represent the audio file by a small set of values called a features vector. In this paper research we will introduce an enhanced method of features extraction based on k-mean clustering. The method will be tested and implemented to show how the proposed method can reduce the efforts of voice identification, and can minimize the recognition time a set of voice extracted features must be used instead of using the voice wave file.

Digital Audio Watermarking Techniques for MP3 Audio Files

2008 ◽  
pp. 205-228
Author(s):  
Dimitrios Koukopoulos
Keyword(s):  
Audio Watermarking ◽  
Digital Audio ◽  
Semantic Meaning ◽  
Audio File ◽  
Digital Audio Watermarking ◽  
Copyright Ownership ◽  
Audio Files ◽  
The Mind ◽  
Watermarking Scheme ◽  
Compressed Data

In this chapter, we will present a brief overview of audio watermarking with the focus on a novel audio watermarking scheme which is based on watermarks with a “semantic” meaning and offers a method for mpeg audio layer 3 files which does not need the original watermark for proving copyright ownership of an audio file. This scheme operates directly in the compressed data domain, while manipulating the time and subband/channel domains and was implemented with the mind on efficiency, both in time and space. The main feature of this scheme is that it offers users the enhanced capability of proving their ownership of the audio file not by simply detecting the bit pattern that comprises the watermark itself, but by showing that the legal owner knows a hard to compute property of the watermark bit sequence (“semantic” meaning). Our discussion on the scheme is accompanied by experimental results.

scholarly journals APLIKASI WATERMARKING DENGAN ALGORITMA AES UNTUK PEMBERIAN DATA HAK CIPTA PADA FILE AUDIO

2015 ◽  
Vol 4 (1) ◽  
Author(s):  
Yusuf Durrachman, Arini, Muhamad Soleh
Keyword(s):  
Data Transmission ◽  
Audio Signal ◽  
Advanced Encryption Standard ◽  
Digital Audio ◽  
Audio File ◽  
Audio Quality ◽  
Transmission Rates ◽  
Attention Focus ◽  
Coding Method ◽  
Audio Files

Watermarking audio files has  recently become the  attention  focus. This is primarily due to faster data transmission rates on the Internet, which has allowed the often illegal proliferation of digital audio files. Watermarking may give the ability to enforce copyright protection of digital audio files products. The difficulties in watermarking audio lie in both the desire to preserve file quality and the need for the watermark to remain intact after a number of possibly damaging file operations. This  topic discusses about watermarking on audio file with AES (Advanced Encryption Standard) – Rinjdael algorithms with embedding procedure and extraction to purpose protection Watermarking method to used embedding process and extraction is low bit coding method. None of the transformations to and from frequency domain are performed either in embedding or extraction part of the proposed scheme.  Testing  process done using 5 ways such as  suitability of process and data, audio quality, audio size  and the last is data robustness, those result showed  that  embedded watermark introduces uncertainly and the embedded watermark into audio signal very is difficult to be detected by human auditory system.   Keywords : Watermarking, AES (Advanced Encryption Standard), low bit coding, audio file, copyright

scholarly journals OPTIMASI KETAHANAN WATERMARKING AUDIO DIGITAL MENGGUNAKAN ALGORITMA RSA DAN MSB

2021 ◽  
Vol 7 (1) ◽  
pp. 45-49
Author(s):  
Benget Rumahorbo ◽  
◽  
Resianta Perangin-angin
Keyword(s):  
Digital Media ◽  
Digital Audio ◽  
Compression Process ◽  
Audio File ◽  
Digital Rights ◽  
Digital World ◽  
Digital File ◽  
Copyright Ownership ◽  
The Right

Copyright is a serious problem in the digital world, the process of sending and distributing digital media is so easy nowadays, copyright in the digital world is very detrimental to those who feel that their digital rights are copied and pasted or taken without the consent of the creator. Therefore we need a way where when a digital file can be identified as original as a product, one of the right ways is to use a watermark technique. But often this watermark process can be lost or cannot be extracted because the digital file has gone through a compression process, duplicate, or something else. So in this study, it will be tried to increase the durability of a watermark in digital audio as a solution for identifying copyrighted digital works. Where the watermark process will use the RSA and MSB algorithms to enter information into a digital audio file, later this information can be extracted to view copyright ownership information from the digital audio. And it is hoped that this watermarking is resistant to various digital audio processes such as compression, duplication, and editing carried out on the file. the information that is inserted into is maintained without compromising the quality of the digital audio.

Clinical Success Using the Audio-Visual Feedback Training for Cluttering

2019 ◽  
Vol 4 (6) ◽  
pp. 1589-1594
Author(s):  
Yvonne van Zaalen ◽  
Isabella Reichel
Keyword(s):  
Visual Feedback ◽  
Clinical Success ◽  
Pause Duration ◽  
Digital Audio ◽  
Male Adolescents ◽  
Feedback Training ◽  
Positive Effects ◽  
Speech Monitoring ◽  
Adolescents And Adults

Purpose Among the best strategies to address inadequate speech monitoring skills and other parameters of communication in people with cluttering (PWC) is the relatively new but very promising auditory–visual feedback (AVF) training ( van Zaalen & Reichel, 2015 ). This study examines the effects of AVF training on articulatory accuracy, pause duration, frequency, and type of disfluencies of PWC, as well as on the emotional and cognitive aspects that may be present in clients with this communication disorder ( Reichel, 2010 ; van Zaalen & Reichel, 2015 ). Methods In this study, 12 male adolescents and adults—6 with phonological and 6 with syntactic cluttering—were provided with weekly AVF training for 12 weeks, with a 3-month follow-up. Data was gathered on baseline (T0), Week 6 (T1), Week 12 (T2), and after follow-up (T3). Spontaneous speech was recorded and analyzed by using digital audio-recording and speech analysis software known as Praat ( Boersma & Weenink, 2017 ). Results The results of this study indicated that PWC demonstrated significant improvements in articulatory rate measurements and in pause duration following the AVF training. In addition, the PWC in the study reported positive effects on their ability to retell a story and to speak in more complete sentences. PWC felt better about formulating their ideas and were more satisfied with their interactions with people around them. Conclusions The AVF training was found to be an effective approach for improving monitoring skills of PWC with both quantitative and qualitative benefits in the behavioral, cognitive, emotional, and social domains of communication.

Digital Audio and Self-Help for People Who Stutter

ASHA Leader ◽  
2008 ◽  
Vol 13 (14) ◽  
pp. 19-19 ◽  
Author(s):  
Greg Snyder ◽  
Peter Reitzes ◽  
Eric Jackson
Keyword(s):  
Digital Audio ◽  
Self Help

CD by radio: digital audio broadcasting

IEE Review ◽  
1992 ◽  
Vol 38 (4) ◽  
pp. 131 ◽  
Author(s):  
Henry Price
Keyword(s):  
Digital Audio ◽  
Digital Audio Broadcasting

Digital audio broadcasting

IEE Review ◽  
1992 ◽  
Vol 38 (6) ◽  
pp. 216
Author(s):  
Edward C. Forster
Keyword(s):  
Digital Audio ◽  
Digital Audio Broadcasting
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