A Framework for Adaptive Real-Time Loudness Control
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A. Alemanno, A. Travaglini, S. Scardapane, D. Comminiello, and A. Uncini, "A Framework for Adaptive Real-Time Loudness Control," Paper 8821, (2013 May.). doi:
A. Alemanno, A. Travaglini, S. Scardapane, D. Comminiello, and A. Uncini, "A Framework for Adaptive Real-Time Loudness Control," Paper 8821, (2013 May.). doi:
Abstract: Over the last few years, loudness control represents one of the most frequently investigated topics in audio signal processing. In this paper we describe a framework designed to provide adaptive real-time loudness measurement and processing of audio files and streamed content being reproduced by mobile players hosted in laptops, tablets, and mobile phones. The proposed method aims to improve the users’ listening experience by normalizing the loudness level of the content in real-time, while preserving the original creative intent of the original soundtrack. The loudness measurement and adaptation is based on a customization of the High Efficiency Loudness Model algorithm described in the AES Convention Paper #8612 (“HELM: High Efficiency Loudness Model for Broadcast Content,” presented at the 132nd Convention, April 2012). Technical and subjective tests were performed in order to evaluate the performance of the proposed method. In addition, the way the subjective test was arranged offered the opportunity to gather information on the preferred Target Level of streamed and media files reproduced on portable devices.
@article{alemanno2013a,
author={alemanno, andrea and travaglini, alessandro and scardapane, simone and comminiello, danilo and uncini, aurelio},
journal={journal of the audio engineering society},
title={a framework for adaptive real-time loudness control},
year={2013},
volume={},
number={},
pages={},
doi={},
month={may},}
@article{alemanno2013a,
author={alemanno, andrea and travaglini, alessandro and scardapane, simone and comminiello, danilo and uncini, aurelio},
journal={journal of the audio engineering society},
title={a framework for adaptive real-time loudness control},
year={2013},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={over the last few years, loudness control represents one of the most frequently investigated topics in audio signal processing. in this paper we describe a framework designed to provide adaptive real-time loudness measurement and processing of audio files and streamed content being reproduced by mobile players hosted in laptops, tablets, and mobile phones. the proposed method aims to improve the users’ listening experience by normalizing the loudness level of the content in real-time, while preserving the original creative intent of the original soundtrack. the loudness measurement and adaptation is based on a customization of the high efficiency loudness model algorithm described in the aes convention paper #8612 (“helm: high efficiency loudness model for broadcast content,” presented at the 132nd convention, april 2012). technical and subjective tests were performed in order to evaluate the performance of the proposed method. in addition, the way the subjective test was arranged offered the opportunity to gather information on the preferred target level of streamed and media files reproduced on portable devices.},}
TY - paper
TI - A Framework for Adaptive Real-Time Loudness Control
SP -
EP -
AU - Alemanno, Andrea
AU - Travaglini, Alessandro
AU - Scardapane, Simone
AU - Comminiello, Danilo
AU - Uncini, Aurelio
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2013
TY - paper
TI - A Framework for Adaptive Real-Time Loudness Control
SP -
EP -
AU - Alemanno, Andrea
AU - Travaglini, Alessandro
AU - Scardapane, Simone
AU - Comminiello, Danilo
AU - Uncini, Aurelio
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2013
AB - Over the last few years, loudness control represents one of the most frequently investigated topics in audio signal processing. In this paper we describe a framework designed to provide adaptive real-time loudness measurement and processing of audio files and streamed content being reproduced by mobile players hosted in laptops, tablets, and mobile phones. The proposed method aims to improve the users’ listening experience by normalizing the loudness level of the content in real-time, while preserving the original creative intent of the original soundtrack. The loudness measurement and adaptation is based on a customization of the High Efficiency Loudness Model algorithm described in the AES Convention Paper #8612 (“HELM: High Efficiency Loudness Model for Broadcast Content,” presented at the 132nd Convention, April 2012). Technical and subjective tests were performed in order to evaluate the performance of the proposed method. In addition, the way the subjective test was arranged offered the opportunity to gather information on the preferred Target Level of streamed and media files reproduced on portable devices.
Over the last few years, loudness control represents one of the most frequently investigated topics in audio signal processing. In this paper we describe a framework designed to provide adaptive real-time loudness measurement and processing of audio files and streamed content being reproduced by mobile players hosted in laptops, tablets, and mobile phones. The proposed method aims to improve the users’ listening experience by normalizing the loudness level of the content in real-time, while preserving the original creative intent of the original soundtrack. The loudness measurement and adaptation is based on a customization of the High Efficiency Loudness Model algorithm described in the AES Convention Paper #8612 (“HELM: High Efficiency Loudness Model for Broadcast Content,” presented at the 132nd Convention, April 2012). Technical and subjective tests were performed in order to evaluate the performance of the proposed method. In addition, the way the subjective test was arranged offered the opportunity to gather information on the preferred Target Level of streamed and media files reproduced on portable devices.
Authors:
Alemanno, Andrea; Travaglini, Alessandro; Scardapane, Simone; Comminiello, Danilo; Uncini, Aurelio
Affiliations:
Sapienza University of Rome, Rome, Italy; Fox International Channels Italy, Guidonia Montecelio (RM), Italy(See document for exact affiliation information.)
AES Convention:
134 (May 2013)
Paper Number:
8821
Publication Date:
May 4, 2013Import into BibTeX
Subject:
Perception
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=16722