This paper describes and compares two offline binaural converting algorithms based on HRTFs (Head-Related Transfer Functions) for 3D audio contents. Recognizing the widespread use of headphones by the typical modern audio content consumer, two strategies to binaurally translate the 3D mixes are explored in order to give a convincing 3D aural experience "on the go." Aiming for the best output quality possible and avoiding the compromises inherent to real-time processing, the paper compares the channel- and the object-based models, notably looking respectively into the spectral analysis of channels for usage of HRTFs at intermediate positions between the virtual speakers and the dynamic convolution of the HRTFs with the objects according to their position coordinates in time.
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