Meeting Topic: Perceptual Implications of Data Compressed Audio
Moderator Name: Kerry Haps
Speaker Name: Dr. Pantelis N. Vassilakis
Meeting Location: chicago
The dual objective of audio data compression algorithms is to reduce the digital file size of audio content for more efficient storage and distribution without audibly altering its quality, as perceived by listeners. The mathematical and psycho-acoustical bases of the relevant algorithms guarantee that, save for simple audio programming (i.e. with narrow bandwidth, dynamic range, and spatial spread and with limited/coarse time variance), audio data compression resulting in 128, 192, and even 256kb/sec data rates will audibly alter the signal in question and irreversibly remove physical aspects usually associated with perceived naturalness and complexity. Exclusive exposure to data compressed audio may deprive listeners from opportunities to be exposed to and therefore stay "trained" in their ability to decipher sonic micro variations that are essential not only to a rich musical experience but to communication in general. Several ways to address this potential problem will be addressed, leading to a discussion of if/how sound signal micro-variation considerations may inform sound recording/mixing decisions.