HAUTH2020
Blind equalization cancellation model

Usage:

out_struct = hauth2020(MixedSig, fs)
out_struct = hauth2020('RequiredSignal',mixed_input,'OptionalSignal',...[OptionalSignal1 OptionalSignal2]...,OptionalSignalN,'model_params',model_params)

Input parameters:

`MixedSig`	two-channel matrix containing signal + noise
`fs`	the sampling frequency of MixedSignal [Hz]

Output parameters:

out_struct

Structure containing the processed signals, in the order [Sel Min Max]

Description:

The SII used in the study by Hauth et al. (2020) requires band specific levels. If optional signals are present, the levels of all optional signals after EC processing and better ear selection are part of the output structure.

Additional input parameters:

`'OptSigs',OptSig`	matrix containing one or more optional two channel signals
`'fmin',fmin`	center frequency of the lowest filter of the gammatone filterbank [Hz]
`'fmax',fmax`	center frequency of the highest filter of the gammatone filterbank [Hz]
`'f_target',f_target`	specified frequency that will have a matched gammatone filter [Hz]
`'ERB_factor',ERB_factor`
	gammatone filter bandwidth

hauth2020 accepts the following flags:

`'binauralinaccuracies'`
	enable binaural processing inaccuracies
`'no_binauralinaccuracies'`
	disable binaural processing inaccuracies
`'longterm'`	SRMR-decision making considers whole signal
`'shortterm'`	blockwise SRMR-decision making based on same time constants as EC and BE processing

Parameter description:

`'RequiredSignal'`	is the mixture of speech and noise, which is a two channel (left,right) matrix (mixed_input)
`'OptionalSignal'`	One or more optional two channel signals, which are processed in the same way as the 'RequiredSignal'. They have to be arranged in a single matrix such that always two columns correspond to the left and right ear signals [left1 right1 left2 right2 ... leftN rightN] (e.g. if you need clean speech and noise for your back-end)
`'model_params'`	Structure containing model parameters like frequency range etc.
`'out_struct'`	Structure containing the processed signals, in the order [Sel Min Max] e.g. out_struct.signals.Mixsigsynfin contains the EC/BE processed mixed signal, where the best strategy was chosen blindly

References:

C. F. Hauth, S. C. Berning, B. Kollmeier, and T. Brand. Modeling binaural unmasking of speech using a blind binaural processing stage. Trends in Hearing, 2020. [ http ]