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Alejandro Osses

Publications and source records attributed to Alejandro Osses.

2 recordsLinked to original sources

Towards a reproducible cross-venue method for quantifying crowd noise in stadiums

Public claims about the loudest stadium have been based on an instantaneous peak dB(A) reading measured at a single point, as popularised by the Guinness World Records "loudest crowd roar" category. The current record dates from 2014, where a maximum level of 142.2 dB(A) was registered. While compelling, those measurements lack standardisation, omitting relevant information such as the specific instrument that was used, the usage of time weighting, and the number of measurement positions that were tested. This lack of information does not allow a well-founded scientific comparison across sport venues. This study proposes a measurement framework in which spatially distributed acoustic measurement is the recommended route for a representative cross-venue comparison, while a single-anchor measurement can only serve as a minimum reporting baseline when distributed measurements are not feasible.

eess.AS

A microscopic investigation of the effect of random envelope fluctuations on phoneme-in-noise perception

In this study, we investigated the effect of specific noise realizations on the discrimination of two consonants, /b/ and /d/. For this purpose, we collected data from twelve participants, who listened to the words /aba/ or /ada/ embedded in one of three background noises. All noises had the same long-term spectrum but differed in the amount of random envelope fluctuations. The data were analyzed on a trial-by-trial basis using the reverse-correlation method. The results revealed that it is possible to predict the categorical responses with better-than-chance accuracy purely based on the spectro-temporal distribution of the random envelope fluctuations of the corresponding noises, without taking into account the actual targets or the signal-to-noise ratios used in the trials. The effect of the noise fluctuations explained on average 8.1% of the participants' responses in white noise, a proportion that increased up to 13.3% for noises with a larger amount of fluctuations. The estimated time-frequency weights revealed that the measured effect originated from confusions between noise fluctuations and relevant acoustic cues from the target words. Substantially similar conclusions were obtained from simulations using an artificial listener. We argue that this token-specific effect of noise is a form of informational masking.

cs.SD