[twoears_benefit, weighted_bmld, weighted_better_ear] = lavandier2022(target_in,int_in,fs)
target_in | target |
int_in | interferer |
fs | sampling frequency [Hz] |
twoears_benefit | effective target to interferer ratio |
weighted_bmld | weighted binaural masking level difference |
weighted_better_ear | |
weighted better ear advantage |
lavandier2022 computes the binaural 'effective' target-to-interferer ratio. target_in and int_in are signals produced at the ears: stereo files (2-column matrices) of the same sampling frequency fs
M. Lavandier, T. Vicente, and L. Prud'homme. A series of snr-based speech intelligibility models in the auditory modeling toolbox. Acta Acustica, 2022.
M. Lavandier, S. Jelfs, J. Culling, A. Watkins, A. Raimond, and S. Makin. Binaural prediction of speech intelligibility in reverberant rooms with multiple noise sources. J. Acoust. Soc. Am., 131(1):218--231, 2012. [ http ]
M. Lavandier and J. Culling. Speech segregation in rooms: Monaural, binaural and interacting effects of reverberation on target and interferer. J. Acoust. Soc. Am., 123(4):2237--2248, 2008. [ http ]
S. Jelfs, J. Culling, and M. Lavandier. Revision and validation of a binaural model for speech intelligibility in noise. Hearing Research, 2011.