{'fraction_non_alphanumeric': 0.016405135520684736, 'fraction_numerical': 0.0, 'mean_word_length': 5.377272727272727, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Cues for masked amplitude-modulation detection.

The ability of psychoacoustic models to predict listeners' performance depends on two key stages: preprocessing and the generation of a decision variable. The goal of the current study was to determine the perceptually relevant decision variables in masked amplitude-modulation detection tasks in which the modulation depth of the masker was systematically varied. Potential cues were made unreliable by roving the overall modulation depth from trial to trial or were reduced in salience by equalizing the envelope energy of the standard and target after the signal was added. Listeners' performance was significantly degraded in both paradigms compared to the baseline (fixed-level modulation masker) condition, which was similar to those used in previous studies of masking in the envelope-frequency domain. Although this observation was broadly consistent with a simple long-term envelope power-spectrum model, there were several aspects of the data that were not. For example, the steep rate of change in threshold with masker depth and the fact that an optimal amount of envelope noise could enhance performance were not predicted by decision variables calculated directly from the stimulus envelope. A physiologically based processing model suggested a realistic nonlinear mechanism that could give rise to these second-order features of the data.