For marine biologists, the interpretation and understanding of underwater audio recordings is essential. Based on such recordings, possible conclusions about behavior, communication and social interactions of marine animals can be made.

Despite a large number of biological studies on the subject of orca vocalizations, it is still difficult to recognize a structure or semantic significance of the orca signals in order to be able to derive any patterns of behavior.

Due to a lack of  techniques and computational tools, hundreds of hours of underwater recordings are still listened to by marine biologists in order to detect potential orca vocalizations. In a post process these identified orca signals will be analyzed and categorized.

The main goal is to provide a robust method which is able to automatically detect orca calls within underwater audio recordings.

A robust detection of orca signals in connection with the associated situational video recordings and behaviour descriptions (provided by several researchers on site) can provide potential information about communication (kind of a language model) and behaviors (e.g. hunting, socializing).

Furthermore, the orca signal detection algorithm can be used in conjunction with a localization software to provide the researchers on the field a more efficient way of searching orca populations.

For more information about the DeepAL project please contact me at christian.bergler@fau.de.