Microphone identification using one-class classification approach

Rapid growth of technical developments has created huge challenges for microphone forensics - a subcategory of audio forensic science, because of the availability of numerous digital recording devices and massive amount of recording data. Demand for fast and efficient methods to assure integrity and authenticity of information is becoming more and more important in criminal investigation nowadays. Machine learning has emerged as an important technique to support audio analysis processes of microphone forensic practitioners. However, its application to real life situations using supervised learning is still facing great challenges due to expensiveness in collecting data and updating system. In this paper, we introduce a new machine learning approach which is called One-class Classification (OCC) to be applied to microphone forensics; we demonstrate its capability on a corpus of audio samples collected from several microphones. Research results and analysis indicate that OCC has the potential to benefit microphone forensic practitioners in developing new tools and techniques for effective and efficient analysis.

Identifying microphone from noisy recordings by using representative instance one class-classification approach

Rapid growth of technical developments has created huge challenges for microphone forensics - a sub-category of audio forensic science, because of the availability of numerous digital recording devices and massive amount of recording data. Demand for fast and efficient methods to assure integrity and authenticity of information is becoming more and more important in criminal investigation nowadays. Machine learning has emerged as an important technique to support audio analysis processes of microphone forensic practitioners. However, its application to real life situations using supervised learning is still facing great challenges due to expensiveness in collecting data and updating system. In this paper, we introduce a new machine learning approach which is called One-class Classification (OCC) to be applied to microphone forensics; we demonstrate its capability on a corpus of audio samples collected from several microphones. In addition, we propose a representative instance classification framework (RICF) that can effectively improve performance of OCC algorithms for recording signal with noise. Experiment results and analysis indicate that OCC has the potential to benefit microphone forensic practitioners in developing new tools and techniques for effective and efficient analysis.

Implementing an online audio lecture streaming facility

This paper describes our experiences in implementing an audio lecture streaming facility for Deakin University. For many years Deakin students have benefited from some of the most comprehensive printed study notes of any university in Australia. In 2002, portable digital audio recorders were utilised by academic staff to capture lecture presentations in order to supplement existing unit learning materials and teaching delivery methods. Audio recordings were processed to enable streamed access via the web browser interface using QuickTime. A trial of incorporating PowerPoint presentations was conducted on a limited basis. 68 undergraduate and postgraduate units implemented lecture streaming. This represented over1700 lecture recordings and 20000 audio streams. Evaluation findings indicate that students find this facility highly valuable to their studies and regularly access the audio recordings throughout semester. Benefits include; access to lecture presentations for off-campus enrolled students, the ability to revisit lecture presentations, and the ability to study at a place and time of convenience. Future enhancement to the audio lecture streaming may include implementing a hard-wired audio capture system into lecture theatres and providing for a more rapid turn around of audio processing.

Teaching digital forensics to undergraduate students

Digital forensics isn't commonly a part of an undergraduate university degree, but Deakin University in Australia recently introduced the subject as part of an IT security course. As instructors, we've found that digital forensics complements our other security offerings because it affords insights into why and how security fails. A basic part of this course is an ethics agreement signed by students and submitted to the unit instructor. This agreement, approved by Deakin University's legal office and consistent with Barbara Endicott-Popovsky's approach, requires students to maintain a professional and ethical attitude to the subject matter and its applications. Assignments regularly cast students in the role of forensic professional. Our teaching team emphasizes throughout the course that professional conduct establishes credibility with employers and customers as well as colleagues, and is required to perform the job effectively. This article describes our experiences with this course.

Analysing audio-recorded data : using computer software applications

Conventional methods of qualitative data analysis require transcription of audio-recorded data prior to conduct of the coding and analysis process. In this paper Alison Hutchinson describes and illustrates an innovative method of data analysis that comprises the use of audio-editing software to save selected audio bytes from digital audio recordings of meetings. The use of a database to code and manage the linked audio files and generate detailed and summary reports, including reporting of code frequencies according to participant code and/or meeting, is also highlighted. The advantage of using this approach in the analysis of audio-recorded data is that the process may be undertaken in the medium in which the data were collected. Though time-consuming, this process negates the need for expensive and time intensive transcription of recorded data.

A novel pseudonoise sequence for time-spread echo based audio watermarking

This paper deals with the problem of digital audio watermarking using echo hiding. Compared to many other methods for audio watermarking, echo hiding techniques exhibit advantages in terms of relatively simple encoding and decoding, and robustness against common attacks. The low security issue existing in most echo hiding techniques is overcome in the timespread echo method by using pseudonoise (PN) sequence as a secret key. In this paper, we propose a novel sequence, in conjunction with a new decoding function, to improve the imperceptibility and the robustness of time-spread echo based audio watermarking. Theoretical analysis and simulation examples illustrate the effectiveness of the proposed sequence and decoding function.

Lunchroom to boardroom : an audio digitization project

The University of Queensland Cybrary in partnership with the Distributed Systems Technology Centre (DSTC), has created a searchable, web based digital oral history resource, based on a collection of stories of women involved in the Queensland Labor movement. A Trades and Labour Council of Queensland oral history collection was used to develop a framework for retrieval of audio materials on the web. A system for linking digitized media files to indexes created from transcripts (Meggie) has been developed. This allows the media file itself to be searched via key words. A trial was conducted and work is now proceeding on completing the collection. The final product will be made available via the Library's web site. The process followed, the choices made, the problems overcome, and the results achieved, will be outlined.

A novel bipolar time-spread echo hiding based watermarking method for stereo audio signals

In this paper, a novel bipolar time-spread (TS) echo hiding based watermarking method is proposed for stereo audio signals, to overcome the low robustness problem in the traditional TS echo hiding method. At the embedding, echo signals with opposite polarities are added to both channels of the host audio signal. This improves the imperceptibility of the watermarking scheme, since added watermarks have similar effects in both channels. Then decoding part is developed, in order to improve the robustness of the watermarking scheme against common attacks. Since these novel embedding and decoding methods utilize the advantage of two channels in stereo audio signals, it significantly reduces the interference of host signal at watermark extraction which is the main reason for error detection in the traditional TS echo hiding based watermarking under closed-loop attack. The effectiveness of the proposed watermarking scheme is theoretically analyzed and verified by simulations under common attacks. The proposed echo hiding method outperforms conventional TS echo hiding based watermarking when their perceptual qualities are similar.

Effective pseudonoise sequence and decoding function for imperceptibility and robustness enhancement in time-spread echo-based audio watermarking

This paper proposes an effective pseudonoise (PN) sequence and the corresponding decoding function for time-spread echo-based audio watermarking. Different from the traditional PN sequence used in time-spread echo hiding, the proposed PN sequence has two features. Firstly, the echo kernel resulting from the new PN sequence has frequency characteristics with smaller magnitudes in perceptually significant region. This leads to higher perceptual quality. Secondly, the correlation function of the new PN sequence has three times more large peaks than that of the existing PN sequence. Based on this feature, we propose a new decoding function to improve the robustness of time-spread echo-based audio watermarking. The effectiveness of the proposed PN sequence and decoding function is illustrated by theoretical analysis, simulation examples, and listening test.

An empirical examination of feedback : user control and performance in a hapto-audio-visual training environment

Utilising advanced technologies, such as virtual environments (VEs), is of importance to training and education. The need to develop and effectively apply interactive, immersive 3D VEs continues to grow. As with any emerging technology, user acceptance of new software and hardware devices is often difficult to measure and guidelines to introduce and ensure adequate and correct usage of such technologies are lacking. It is therefore imperative to obtain a solid understanding of the important elements that play a role in effective learning through VEs. In particular, 3D VEs may present unusual and varied interaction and adoption considerations. The major contribution of this study is to investigate a complex set of interrelated factors in the relatively new sphere of VEs for training and education. Although many of the factors appears to be important from past research, researcher have not explicitly studied a comprehensive set of inter-dependant, empirically validated factors in order to understand how VEs aid complex procedural knowledge and motor skill learning. By integrating theory from research on training, human computer interaction (HCI), ergonomics and cognitive psychology, this research proposes and validates a model that contributes to application-specific VE efficacy formation. The findings of this study show visual feedback has a significant effect on performance. For tactile/force feedback and auditory feedback, no significant effect were found. For satisfaction, user control is salient for performance. Other factors such as interactivity and system comfort, as well as level of task difficulty, also showed effects on performance.

Wearing your PIM : experiments with an audio enhanced PIM

PIM systems help organise people’s lives by providing address book, schedule and task management facilities. Current PIM’s manage this information by collecting and storing it as textual data. With the advent of the wearable computer, using text only is no longer an efficient and convenient mechanism for managing personal information. A wearable computer should use data from various sensors (video, audio, location, environmental, user state) to organise personal information. In this paper we examine how audio can be used to enhance the facilities provided by text-only PIM’s and present an example implementation of an audio based wearable PIM (wPIM) that has the capability of storing and retrieving PIM information as audio recordings. The results of the user evaluation we conducted, which was carried out outside of the laboratory, suggests that users strongly accept audio as a way to manage their personal information and to augment their memory, supporting our hypothesis that audio enhances wearable personal information management.

Echo hiding based stereo audio watermarking against pitch-scaling attacks

In audio watermarking, the robustness against pitch-scaling attack, is one of the most challenging problems. In this paper, we propose an algorithm, based on traditional time-spread(TS) echo hiding based audio watermarking to solve this problem. In TS echo hiding based watermarking, pitch-scaling attack shifts the location of pseudonoise (PN) sequence which appears in the cepstrum domain. Thus, position of the peak, which occurs after correlating with PN-sequence changes by an un-known amount and that causes the error. In the proposed scheme, we replace PN-sequence with unit-sample sequence and modify the decoding algorithm in such a way it will not depend on a particular point in cepstrum domain for extraction of watermark. Moreover proposed algorithm is applied to stereo audio signals to further improve the robustness. Experimental results illustrate the effectiveness of the proposed algorithm against pitch-scaling attacks compared to existing methods. In addition to that proposed algorithm also gives better robustness against other conventional signal processing attacks.