Abstract: Embodiments of the present invention relate to audio object clustering by utilizing temporal variation of audio objects. There is provided a method of estimating temporal variation of an audio object for use in audio object clustering. The method comprises obtaining at least one segment of an audio track associated with the audio object, the at least one segment containing the audio object; estimating variation of the audio object over a time duration of the at least one segment based on at least one property of the audio object and adjusting, at least partially based on the estimated variation of the audio object, a contribution of the audio object to the determination of a centroid in the audio object clustering. Corresponding system and computer program product are disclosed.

Abstract: Audio objects that are present in input audio content in one or more frames are determined. Output clusters that are present in output audio content in the one or more frames are also determined. Here, the audio objects in the input audio content are converted to the output clusters in the output audio content. One or more spatial error metrics are computed based at least in part on positional metadata of the audio objects and positional metadata of the output clusters.

Abstract: Embodiments are directed a method of rendering object-based audio comprising determining an initial spatial position of objects having object audio data and associated metadata, determining a perceptual importance of the objects, and grouping the audio objects into a number of clusters based on the determined perceptual importance of the objects, such that a spatial error caused by moving an object from an initial spatial position to a second spatial position in a cluster is minimized for objects with a relatively high perceptual importance. The perceptual importance is based at least in part by a partial loudness of an object and content semantics of the object.