The process of mixing tracks for a live stage performance or studio session is both time consuming and expensive with assistance of professionals. It is also difficult for individuals to remain competitive against established companies, since multiple tracks must be properly mixed in order to achieve well-enhanced elements -- generally, a poor mix makes it difficult for the listener to distinguish the different elements of the mix. The developed method during this thesis work aims at facilitating the mixing work for live performances and studio sessions. The implemented system analyzes the energy spectrum of the tracks included in the mix. By unmasking spectral components, the spectral overlap of the tracks is minimized. The system filters non-characteristic frequencies, leaving significant frequencies undisturbed. Five tracks have been used from the final mix of a successful radio song. These tracks have been analyzed and used to illustrate and validate the developed method. The system was successfully implemented in MATLAB with promising results and conclusions. The processed mix unmasks frequency content and is perceived to sound clearer compared to the unprocessed mix by a number of test individuals. The method reminds of a multi-band compressor that analyzes the spectral information between tracks. Thus, by use of inter-spectral dependencies, the thesis investigates the possibility to control the amplitudes in time by filtration in frequency domain. The compression rate in time domain is reflected in regard to a trade-off between conservation of characteristic frequencies and reduction of spectral overlaps.

The increasing interest for immersive experiences in areas such as augmented and virtual reality makes high quality 3D sound more important than ever before. A technique for capturing and rendering 3D audio which has received more attention during the last twenty years are Higher Order Ambisonics (HOA). Higher Order Ambisonics is a scene based audio format which has a lot of advantages compared to other standard formats. Hovever, one problem with HOA is that it requires a lot of bandwidth. For example, sending an uncoded high quality HOA signal requires 49 channels to be transmitted at the same time which requires a bandwidth of about 40 Mbps. A lot of effort has been made in the last ten years on coding HOA signals. In this thesis, two different approaches are taken on coding HOA signals. In one approach, called Sound Field Rotation (SFR) in this thesis, the microphone that records the sound field is virtually rotated to see if it is possible to make some of the channels zero. The second approach, called Sound Field Decomposition (SFD) in this thesis, use Principal component analysis to decompose a sound field into a foreground and background component. The Sound Field Decomposition approach is inspired by the emerging MPEG-H 3D Audio standard for coding HOA signals. The result shows that the Sound Field Rotation method only works for very simple sound scenes. It has also been shown that a 49 channels HOA signal can be reduced to as little as 7 channels if the sound scene consists of a point source. The Sound Field Deomposition method worked for more complex sound scenes. It was shown that a MPEG similar system could be improved. Result from MUSHRA (Multiple stimuli with hidden reference and anchor) listening tests showed that an improved MPEG similar system reached a MUSHRA score about 78 while the MPEG similar system reached 55 at a bitrate of 256 kbps. Without coding each monochannels with the 3GPP EVS (Enhanced voice services) codec, the improved MPEG similar system reached the MUSHRA score 85. At 256 kbps, the improved MPEG similar system coded the HOA signal into six channels instead of 49 for the uncoded signal. From objective results, it was shown that the improved MPEG similar system had largest effect at low bitrates.