Performance evaluation of perceptible impulsive noise detection methods based on auditory models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00381399" target="_blank" >RIV/68407700:21230/25:00381399 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1186/s13636-024-00389-9" target="_blank" >https://doi.org/10.1186/s13636-024-00389-9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s13636-024-00389-9" target="_blank" >10.1186/s13636-024-00389-9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Performance evaluation of perceptible impulsive noise detection methods based on auditory models

Popis výsledku v původním jazyce

Reference-free audio quality assessment is a valuable tool in many areas, such as audio recordings, vinyl production, and communication systems. Therefore, evaluating the reliability and performance of such tools is crucial. This paper builds on previous research by analyzing the performance of four additional algorithms in detecting perceptible impulsive noise (clicks) based on auditory models. We compared the results of eight algorithms, hypothesizing that computationally simpler algorithms could perform as well as more complex ones. We obtained a set of audio signals, with and without clicks, annotated by human subjects from a publicly available dataset. Audio signal sets are categorized based on the obtained annotation results to train the algorithms for different levels of the experiments. Experiments containing cross-validation are done for multiple parameters of algorithms. The algorithm training is based on maximizing a discriminability metric (A '). Evaluation criteria of the algorithms included the hit rate, false alarm rate, A ', and computational time. Our findings indicate that computationally simpler auditory models have performed as well as computationally more complex ones, while conventional models exhibit lower performance. Conclusively, the ERBlet transform based algorithm demonstrated superior performance in terms of A ' and robustness. This paper provides insights into the capabilities of auditory models in a practical use case of perceptible click detection. The results presented here can help research and develop such algorithms for vinyl production, audio archiving, podcasting, music production, and telecommunications.

Název v anglickém jazyce

Performance evaluation of perceptible impulsive noise detection methods based on auditory models

Popis výsledku anglicky

Reference-free audio quality assessment is a valuable tool in many areas, such as audio recordings, vinyl production, and communication systems. Therefore, evaluating the reliability and performance of such tools is crucial. This paper builds on previous research by analyzing the performance of four additional algorithms in detecting perceptible impulsive noise (clicks) based on auditory models. We compared the results of eight algorithms, hypothesizing that computationally simpler algorithms could perform as well as more complex ones. We obtained a set of audio signals, with and without clicks, annotated by human subjects from a publicly available dataset. Audio signal sets are categorized based on the obtained annotation results to train the algorithms for different levels of the experiments. Experiments containing cross-validation are done for multiple parameters of algorithms. The algorithm training is based on maximizing a discriminability metric (A '). Evaluation criteria of the algorithms included the hit rate, false alarm rate, A ', and computational time. Our findings indicate that computationally simpler auditory models have performed as well as computationally more complex ones, while conventional models exhibit lower performance. Conclusively, the ERBlet transform based algorithm demonstrated superior performance in terms of A ' and robustness. This paper provides insights into the capabilities of auditory models in a practical use case of perceptible click detection. The results presented here can help research and develop such algorithms for vinyl production, audio archiving, podcasting, music production, and telecommunications.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

EURASIP Journal on Audio Speech and Music Processing

ISSN

1687-4722

e-ISSN

1687-4722

Svazek periodika

2025

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

15

Strana od-do

1-15

Kód UT WoS článku

001421406900001

EID výsledku v databázi Scopus

2-s2.0-85217463285