Loudness vs. Speech Normalization in Film and Drama for Broadcast

2009

This article describes one of the most fundamental changes in the history of audio in broadcasting: the change of the levelling paradigm from peak normalisation to loudness normalisation. This change is vital because of a problem that has become a major source of irritation for television and radio audiences around the world – that of the jump in audio levels at the breaks within programmes, between programmes and between channels. Loudness normalisation is the solution to counteract this problem.

2012

In this paper, we propose a new algorithm for measuring the loudness levels of broadcast content. It is called the High Efficiency Loudness Model (HELM) and it aims to provide robust measurement of programs of any genre, style and format, including stereo and multichannel audio 5.1 surround sound. HELM was designed taking into account the typical conditions of the home listening environment and it is therefore particularly good at meeting the needs of broadcast content users. While providing a very efficient assessment of typical generic programs, it also successfully approaches some issues that arise when assessing unusual content such as programs heavily based on bass frequencies, wide loudness range programs and multi-channel programs as opposed to stereo ones. This paper details the structure of HELM, including its channel-specific frequency weighting and recursive gating implementation. Finally, we present the results of a mean opinion score (MOS) subjective test that demonstrates the effectiveness of the proposed method.

Acta Physica Polonica A, 2010

Popularity of television and multitude of commercials during the TV broadcast lead to the analysis of its sound levels. Costs of commercials' time cause producers to make commercials much louder than a regular TV program. The article shows results of commercials and regular program sound level (RMS and FFT) analysis and the difference in sound levels of commercials compared to a regular program. The analysis also shows the difference between public and private TV. The authors of the article suggest a solution to this problem and its effects.

This paper introduces a novel concept SNORM (Step NORMalization) for increasing normalization. It is a prototype algorithm for increasing normalization based on loudness factor of the audio. The function effect normalization plays a vital role in loudness control. The proposed experiment carried out for increasing normalization based on step wise increase yield the variations in peaks of the audio file. The experimental results are shown in the form of graphical analysis of the plot spectrum values of frequency analysis. From the results, it is clearly apparent that, the normalization values are increased at different levels. The function SNORM can set a new benchmark in the field of audio industry for the processes of increasing normalization. SNORM can be substantial in the audio broadcast systems for applications in live audio streaming, news broadcast, sports coverage, live programming where the loudness control mechanism is essential. For the selective or predictive loudness control systems SNORM can be effectively applied.

The Journal of the Acoustical Society of America, 2016

A model for the loudness of time-varying sounds [Glasberg and Moore (2012). J. Audio. Eng. Soc. 50, 331-342] was assessed for its ability to predict the loudness of sentences that were processed to either decrease or increase their dynamic fluctuations. In a paired-comparison task, subjects compared the loudness of unprocessed and processed sentences that had been equalized in (1) root-mean square (RMS) level; (2) the peak long-term loudness predicted by the model; (3) the mean long-term loudness predicted by the model. Method 2 was most effective in equating the loudness of the original and processed sentences.

After well over a decade of research, discussion and collaboration, the foundations are in place for loudness management across a broad spectrum of delivery platforms. The ITU’s BS.1770-3 is a recommended standard for television and a basis for future discussion regarding loudness management of radio, IP streaming and file–based playback in the home and on mobile platforms. The definition of entertainment is changing, as young audiences do not differentiate between platforms and delivery methods. New tools and methodologies to deliver compliant audio are available that retain quality without sacrificing productivity.

2013

After decades of deep investigation, the international broadcasting community represented by technical associations and bodies has set precise standards aimed to objectively assess loudness levels of programmes. Although all standards rely on the same algorithm as described in ITU-R BS1770, there are still two possible ways to implement such metering, including Voice Detection and Gating. These two different implementations might, in some cases, provide measurements that significantly differ from each other. Furthermore, whilst the gating feature is uniquely defined in the updated version of BS1770-3, Voice Detection is not currently specified in any standard and its implementation is independently designed by manufacturers. This paper analysis this scenario by comparing the results and robustness provided by three different loudness meters based on Voice Detection. In addition, those values are compared with measurements obtained by using BS1770-3 compliant loudness meters, including tables, comments, and conclusions.

2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2012

This paper presents dual sensor based management system for television viewing at home environment in compliance with BS1770 loudness measurement standard aim of the research was mainly to address the issue of sudden increase in loudness during commercials in between TV programmes. Same approach works for any well. The scope of this research reported here investigate, develop an adaptive loudness control system to create a pleasurable TV viewing environment and to algorithm functionality by simulations. The novel made in paper are the design and the proof of functional efficacy of the loudness management algorithms using the measurements made through the simple instrumentation set in compliance with BS1770 loudness measurement

Applied Sciences

While mixing, sound producers and audio professionals empirically set the speech-tobackground ratio (SBR) based on rules of thumb and their own perception of sounds. There is no guarantee that the speech content will be intelligible for the general population consuming content over a wide variety of devices, however. In this study, an approach to automatically determine the appropriate SBR for a scene using an objective intelligibility metric is introduced. The model-estimated SBR needed for a preset minimum intelligibility level was compared to the listener-preferred SBR for a range of background sounds. It was found that an extra gain added to the model estimation is needed even for listeners with normal hearing. This gain is needed so an audio scene can be auditioned with comfort and without compromising the sound effects contributed by the background. When the background introduces little informational masking, the extra gain holds almost constant across the various background sounds. However, a larger gain is required for a background that induces informational masking, such as competing speech. The results from a final subjective rating study show that the model-estimated SBR with the additional gain, yields the same listening experience as the SBR preferred by listeners.

Acta Acustica united with Acustica, 2013

The influence of different properties of speech-likesignals on loudness wasinvestigated by measuring levels at equal loudness in normal-hearing listeners for 22 speech-likes timuli using categorical loudness scaling and an adaptive matching procedure. Eight of the stimuli, referred to as unprocessed stimuli, had the same speech-like long-term spectrum, butdiffered in other speech-related properties, ranging from astationary noise overspeechmodulated signals to real intelligible and unintelligible speech. The other stimuli were designed to investigate the influence of severe modifications of speech-related properties due to spectral filtering, reverberation, compression, and expansion on loudness. In general, results were similar for both measurement methods and revealed only small effects of temporal modulations on loudness perception, and no influence of intelligibility or reverberation. Even severe modifications of the stimuli by highpass-filtering and expansion did not affect levels at equal loudness. Only lowpass-filtering significantly decreased loudness and compression significantly increased loudness. The experimental results indicate that the long-term spectrum of speech has amajor influence on loudness while other properties of speech only have aminor contribution. Some of the results could not be predicted by loudness models based on short-term loudness. Instead, longer time constants were required to not overestimate the loudness of time-varying speech-likesounds.