Audio verification: how to detect editing and substitution in audio recordings
The authenticity of an audio recording can now be questioned as often as photos on the Internet. The key task during verification is not only to find traces of editing, but also to determine their nature, distinguishing technical defects from deliberate falsification. This difference directly determines whether the record can be trusted as evidence or as a source of information.
The ability to identify editing in audio recordings is an important task. At the same time, it is important not only to find traces of editing, but to understand its purpose. The difference between removing interference and intentionally distorting content is fundamental, since the final assessment of all information depends on it. Depending on the type of changes, different terms are used in expert practice to indicate them.:
Audio recording editing is the process of rewriting, in which fragments from one or more phonograms are combined into a new composition. During this process, the order of the fragments can change, as well as the recorded information itself can be edited (for example, by deleting words or parts of a conversation).
The key condition for the editing is the presence of intent — the person performing it acts purposefully, selecting and connecting fragments.
Non-situational changes are a broader concept than “editing”, since they imply any inconsistencies between the actual content of the phonogram and the stated conditions for its creation.
For example, there is no beginning or end on the soundtrack (the conversation starts/ends unexpectedly), while there is information that the recording should have started when the person turned on the recorder and entered the room. Or it is claimed that the recording was made on a mobile phone recorder, but there is no relevant information in the metadata of the file containing the soundtrack.
Other changes are various violations of the continuity of the recording made during the recording process or after its completion, not related to purposeful editing of the content.
For example, there are signs of selective fixation when the pause button is pressed during recording, or when writing using a device that independently pauses and removes the recording (depending on the presence of a speech signal “audible” to the device), or various technical failures (clicks, signal drops) that disrupt the continuity of the audio signal, but at the same time, they are not the result of installation.
Methods for detecting editing in audio recordings
- Analysis of the technical characteristics of the file
– Metadata study: allows you to detect traces of editing by analyzing the history in the file structure. For example, the metadata may contain information about the date and time when the record was created, as well as the software used.
– Formatting and encoding research: Sometimes editing can leave traces in recording formats or encodings. For example, there is a discrepancy between the technical parameters of the recording and the declared format.
- Analysis of sound characteristics
– Study of the continuity of the sound stream: allows you to identify traces of editing through the analysis of anomalies, such as a violation of smoothness and the appearance of atypical pauses.
– Sound distortion: Changing or editing an audio file may cause the sounds to be distorted. For example, unusual noises, jumps in dynamics, or changes in the timbre of a voice.
– Comparison with original specifications (if available): In some cases, it may be possible to compare the characteristics of a recording with its unedited counterparts in order to identify inconsistencies.
- Checking joints and transitions
– Identification of installation traces: artificial transitions or joints may appear during the installation of the recording. They are revealed, for example, through differences in recording quality, noise, or background.
– Identification of the “seams” between fragments: when an audio file is sliced and glued, characteristic traces may remain at the joint, such as noise or short-term changes in sound characteristics.
- Background and noise analysis
– Background noise presence: Most audio recordings have background noise that appears due to the environment, recording technique, or other factors. If the recording has been edited, anomalies in the background noise distribution may be detected. For example, sudden changes in background sounds or their absence in some fragments of a single recording.
- Voice identification and speech analysis
– Speech and voice comparison: analysis of the dialogue for mounting inserts that hide or distort the words of the participants. For example, a violation of the synchronicity of speech, sudden changes in intonation or tempo, indicating artificial interference.
– Definition of temporal characteristics of speech: allows you to identify traces of editing through the analysis of unnatural changes, such as impaired smoothness of speech tempo and artificial pauses.
- Using specialized programs and tools
Specialized programs and tools for analyzing audio files can be used to detect editing. For example, programs for spectrographic analysis that allow you to identify hidden signs of recording processing, such as changes in the frequency spectrum in certain areas, compression artifacts, signs of overlapping or copying fragments.
- Comparative analysis with the original (if available)
If there is an original version of the recording or similar recordings, a comparative analysis will determine whether changes have been made to the file.
Methods for determine the actual date of creation of an audio recording
To determine the exact date and time of recording an audio file, various methods are used to establish the actual date of recording creation:
- Audio file metadata analysis
The metadata of the file contains information that may indicate manipulation.
– Date and time of recording: allows you to set when the recording was made, if the file has not been changed after its creation.
– Edit check: If a record has been edited, the metadata can show the changes, such as the date of the last edit.
- Analysis of recording parameters and characteristics
– File format and Encoding research: Some audio files may contain time information related to encoding formats and methods. For example, when using certain recording formats (WAV, MP3), you can find out the file creation time based on encoding features.
– Comparison with typical recording device characteristics: Devices such as voice recorders or smartphones can record files with certain technical characteristics (sampling rate, bitrate). These characteristics may provide indirect indications of the recording time if they correspond to a specific device model.
- Use of reference records
It may help to set the actual recording date if you have access to other audio files created by the same device during the same time period. For example, if there are recordings made with the same recorder, you can check the time parameters of these recordings to establish a match with the expected date of the audio file.
- Checking the record for changes
– Comparative analysis: Comparing recordings with similar audio files to identify differences in recording quality.
– Time distortion: Check for time distortion that may occur during installation or recording time changes. For example, speeding up or slowing down the recording.
- Comparative analysis of background noise and sound events
Analyzing the audio background of the recording can also help you determine the actual date. For example, by studying the sounds in the background and comparing them with known events or time frames (time of day, the presence of certain noises).
Identifying the editing requires a comprehensive approach. Only cross-checking with different methods will answer the key question: whether the identified changes are accidental or intentional. The answer may be crucial to the entire investigation.