Topic
Audio editing software
About: Audio editing software is a research topic. Over the lifetime, 29 publications have been published within this topic receiving 262 citations. The topic is also known as: sound file editor & sound editor.
Papers
22 Sep 2008
TL;DR: This piece of work is the first one to investigate digital forensics on MP3 format and demonstrates the validity of the proposed approach on detecting some common forgeries, such as deletion, insertion, substitution and splicing.
Abstract: MP3 is the most popular compressed audio format in our daily life but it can be doctored very easily by pervasive audio editing software. Thus it is necessary to develop authentication methods for MP3. Different from JPEG compression for image, MP3 compression has its own characteristics. Thus existing forensics methods for JPEG compression is unable to be applied to MP3 compression directly. In this paper, we propose a passive approach to detect doctored MP3 audio by checking frame offsets. As the audio samples are divided into frames to encode, each frame has its own frame offset after encoding. Forgeries lead to the broken of frame grids. So the frame offsets are good indication for locating forgeries, and the frame offsets can be detected by the identification of quantization characteristic. In this way, the doctored positions can be automatically located. Experimental results demonstrate the validity of the proposed approach on detecting some common forgeries, such as deletion, insertion, substitution and splicing. Under different bitrates, the detection ratios are above 94%. To the best of our knowledge, this piece of work is the first one to investigate digital forensics on MP3 format.
91 citations
TL;DR: This piece of work is the first one to detect double compression of audio signal and uses support vector machine classifiers with feature vectors formed by the distributions of the first digits of the quantized MDCT (modified discrete cosine transform) coefficients.
Abstract: MP3 is the most popular audio format nowadays in our daily life, for example music downloaded from the Internet and file saved in the digital recorder are often in MP3 format. However, low bitrate MP3s are often transcoded to high bitrate since high bitrate ones are of high commercial value. Also audio recording in digital recorder can be doctored easily by pervasive audio editing software. This paper presents two methods for the detection of double MP3 compression. The methods are essential for finding out fake-quality MP3 and audio forensics. The proposed methods use support vector machine classifiers with feature vectors formed by the distributions of the first digits of the quantized MDCT (modified discrete cosine transform) coefficients. Extensive experiments demonstrate the effectiveness of the proposed methods. To the best of our knowledge, this piece of work is the first one to detect double compression of audio signal.
52 citations
19 Apr 2015
TL;DR: A robust pitch tracking method is used to extract the pitch of every syllable and calculate the similarities of these pitch sequences so that it can be used to detect copy-move forgeries of digital audio recording.
Abstract: The widespread availability of audio editing software has made it very easy to create forgeries without perceptual trace. Copy-move is one of popular audio forgeries. It is very important to identify audio recording with duplicated segments. However, copy-move detection in digital audio with sample by sample comparison is invalid due to post-processing after forgeries. In this paper we present a method based on pitch similarity to detect copy-move forgeries. We use a robust pitch tracking method to extract the pitch of every syllable and calculate the similarities of these pitch sequences. Then we can use the similarities to detect copy-move forgeries of digital audio recording. Experimental result shows that our method is feasible and efficient.
48 citations
Proceedings Article•
1 Jan 2007
TL;DR: An “intelligent audio editor” uses a machine-readable score as a specification for the desired performance and automatically makes adjustments to note pitch, timing, and dynamic level.
Abstract: Audio editing software allows multi-track recordings to be manipulated by moving notes, correcting pitch, and making other fine adjustments, but this is a tedious process. An “intelligent audio editor” uses a machine-readable score as a specification for the desired performance and automatically makes adjustments to note pitch, timing, and dynamic level.
33 citations
4 May 2014
TL;DR: This paper proposes a method based on deep learning algorithm and a majority voting strategy that is effective to detect the double compressed AMR audio and the potential application of this technique is discussed.
Abstract: The Adaptive Multi-Rate (AMR) audio codec is a widely used audio data compression scheme optimized for speech and adopted by many devices. With the audio editing software, it is easy to perform tampering on digital speech recording, which makes the audio forensics become an important and urgent issue. Usually, the tampered AMR audio is double compressed AMR audio. In this paper, we proposed a method to detect the double compressed AMR audio. Such technique may be served as a tool for authenticating the originality of audio recordings and detecting the forgery positions. Our proposed method is based on deep learning algorithm and a majority voting strategy is designed for decision. The experimental results show that our method is effective to detect the double compressed AMR audio. Besides, the potential application of this technique is also discussed.
31 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 1 |
| 2020 | 1 |
| 2019 | 2 |
| 2018 | 3 |
| 2017 | 3 |
| 2016 | 6 |