The continued development of the Apple® iOS Voice Memos Application has seen the addition of an increased number of features, allowing users to edit a recording without having to export and process said recording in other software. This subsequently reduces the traces left by a manipulation, so research into the detection of edits performed within the application is therefore vital. Previous research into this area has shown differences in bit-rate between original and edited recordings within the application, and this research builds on that foundation by analyzing the artifacts left through extrapolation. Findings show that a sequence of processes, encompassing three stages of analysis, can be applied to detect local edit points pertaining to delete, replace and long pause events. The first stage is a global analysis used to sequester recordings which contain one of the aforementioned events, before two local analyses, based on different approaches, are applied to provide the location of edit points.
(See document for exact affiliation information.)
https://aes2.org/publications/elibrary-page/?id=20463
(480KB)
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member Join the AES. If you need to check your member status, login to the Member Portal.
