Due to the much publicized loudness wars, we now have a standard to measure loudness: the EBU R128 specification. This is a look at how this standard applies to sound engineers doing live audio or recording for various broadcast media.
Telephone audio sounds reasonably good on most news interviews. But, often, annoying hum and buzz is found in telephone recordings. Where does it come from and what can be done about it?
Like most everything else these days, microphone wind protection has become a complex subject. There are many variations of wind protection equipment now on the market and some of it costs more than the microphones themselves. Guidance may be necessary for television news reporters who work on their own in the field and need protection against strong wind, but don’t want to handle unwieldy gear.
From production to newsgathering and on to international distribution, the media industry relies more on the ability to quickly and easily transfer large files over long distances. Original methods for doing this, like FTP, are unsuited for today’s large file sizes and complex workflows - what is needed is an efficient and secure way to transfer large files in a timely manner. This White Paper from Signiant is a guide to the selection of large file transfer software.
There is no right or wrong way to do audio recording. It is equal parts art and science. One engineer may be very precise in the setup of his gear, while another just goes by feel. Both ways can provide outstanding results. However, there are some basic guidelines that can help you always capture high-quality recordings.
Today’s broadcast engineers face a unique challenge, one that is likely unfamiliar to these professionals. The challenge is to design, build and operate IP-centric solutions for video and audio content.
The SMPTE timecode standard has served us well for almost half a century. But the equipment it was designed for is history, and soon it will be too. The industry needs a replacement.
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Deep learning technology is more common than one might think. This technology is used to identify objects in images, texts or audio, achieving results that were not possible before. This article will examine how deep learning is revolutionizing sports production to enable low-cost, fully automated production for semi-professional and amateur sports broadcasts.
