Multichannel audio synthesis by subband-based spectral conversion and parameter adaptation
Multichannel audio can immerse a group of listeners in a seamless aural environment. Previously, we proposed a system capable of synthesizing the multiple channels of a virtual multichannel recording from a smaller set of reference recordings. This problem was termed multichannel audio resynthesis and the application was to reduce the excessive transmission requirements of multichannel audio. In this paper, we address the more general problem of multichannel audio synthesis, i.e., how to completely synthesize a multichannel audio recording from a specific stereophonic or monophonic recording, which would significantly enhance the recording's acoustic impression. We approach this problem by extending the model employed for the resynthesis problem. This is accomplished by adapting the resynthesis conversion parameters to the statistical properties of the recording that we wish to enhance. This parameter adaptation is similar to the task adaptation employed in speech recognition, when a specific model is applied to a different environment (speaker, language or channel). One particular approach to this problem is shown here to be quite advantageous toward solving the multichannel audio synthesis problem as well.