THE AUDITORY MODELING TOOLBOX

This documentation applies to the most recent AMT version (1.6.0).

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VICENTE2020NH
Compute the effective SNR taking into account better ear and bmld advantages

Usage:

[predicted_SNR, BE, BU] = vicente2020nh(target_in,int_in,fs)

Input parameters:

target_in target
int_in interferer
fs sampling frequency [Hz]

Output parameters:

predicted_SNR SNR predicted by the model
BE better-ear advantage
BU binaural masking level difference advantage

Description:

vicente2020nh computes the effective SNR taking into account BU and BE by respective time frames, taking the target and interferer signals (sampled at fs) as inputs

References:

M. Lavandier, T. Vicente, and L. Prud'homme. A series of snr-based speech intelligibility models in the auditory modeling toolbox. Acta Acustica, 2022.

T. Vicente and M. Lavandier. Further validation of a binaural model predicting speech intelligibility against envelope-modulated noises. Hearing Research, 390(107937), 2020. [ http ]