Referring now to FIG. 6, a process flow diagram of a modeling routine 600 is shown. In accordance with certain aspects of the present disclosure, routine 600 may be implemented or otherwise embodied as a component of a spatial audio processing system; for example, spatial audio processing system 100 as shown and described in FIG. 1. According to an embodiment, modeling routine 600 is initiated by inputting or selecting one or more audio segments during which a target sound source is active (e.g. as a modeling segment) 602 to derive a target audio input or training audio input. In the context of modeling routine 600, this may be referred to as “glimpsing” the training audio data. The one or more audio segments (i.e. the “glimpsed” audio data) may be derived from a live or recorded audio input 612 corresponding to an acoustic location or environment (e.g. an interior room in a building, such as a conference room or lecture hall). In certain embodiments, modeling routine 600 is initiated by designating one or more audio segments during which a source location signal is active as a modeling segment 602. In certain embodiments, the one or more audio segments to be modeled can be designated manually (i.e. selected) or may be designated algorithmically and/or through a Rules Engine or other decision criteria, such as source location estimation, audio level, or visual triggering. In certain embodiments where visual triggering is employed, a spatial audio processing system (e.g. as shown and described in FIG. 1) may include a video camera or motion sensor configured to identify activity or sound source location as a trigger for designating the audio segment.
