Re: The Amazing Spider Man Movies Dual Audio Eng Hindi 720p Torrent PATCHED
Nelson Suggs
Rde, the Australian audio equipment company, recently announced its Wireless PRO wireless microphone system. Rde is calling it the 'most powerful compact microphone system ever.' Despite its diminutive size, it offers a versatile range of professional features to address the needs of demanding filmmakers and video creators, including timecode sync, intelligent GainAssist technology and over 40 hours of onboard recording time.
One of the standout new features of the Wireless PRO system is its built-in 32-bit float audio recording capabilities, a technology we've previously argued should come to hybrid cameras and something that Rde's consumer-grade wireless mics lack.
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Touted as a feature that lets you avoid clipping from loud audio and recover audio that's too quiet without noise, 32-bit float audio seems too good to be true. It essentially frees you from having to set recording levels on your camera or audio recorder.
Before diving into the details, a simple analogy as to what 32-bit float audio is will give you the gist of what this technology allows. To put it in photo terms it's a little bit like moving from JPEG to Raw capture, with all the extra flexibility it brings, but this is a very loose analogy. In digital photography, sensors clip completely when they receive too much light, and all of the data output is typically encoded into the Raw file. In audio recording, microphones can continue to respond even to incredibly loud sounds: it's the process of squeezing it into the digital file that imposes the most significant limitation.
32-bit float provides a vast increase in the available space to record louder sound. In simple terms, fixed point audio records its data values as simple numbers, whereas floating point math records its data as scientific notation.
An example of clipping of a digital waveform. The red lines indicate full scale, and the waveform is shown before and after hard clipping (grey and black outlines, respectively). 32-bit float allows you to capture way beyond the traditional 'full scale' limits.
So, whereas in 16-bit, the audio standard for CDs, you have 65,535 values per sample. With 24-bit audio, the overall idea is similar, but more values per sample are available, at over 16 million. You have much more space for audio information with the 24-bit format.
When audio is recorded in 16-bit or 24-bit, the recording can clip if something gets too loud. The audio will sound distorted, just like the white point in your photos clipping. The sound values are just too much for the audio format to store all that information. In other words, the dynamic range of the audio container is too narrow. A 16-bit fixed point audio file has a calculated maximum dynamic range of 96.3 dB (-96.3 db up to 0 dB), and a 24-bit fixed point has a maximum dynamic range of 144.5 dB (-144.5 dB up to 0 dB). However, whereas using 32-bit fixed point would boost this to 192 dB, using scientific notation allows you to encode vastly large values, and the potential dynamic range expands to a whopping 1,528 dB.
This extreme latitude afforded by 32-bit float audio leads to the notion that video creators never have to worry about audio levels again. To a certain degree, that's true, but it's not quite that simple. With 32-bit float audio recorders, like the Rde Wireless PRO mic kit, Sound Devices MixPre-10 II recorder or TASCAM's Portacapture X8 recorder, for example, it's true that you don't necessarily need to adjust audio levels on the recorder in 32-bit float mode prior or during recording.
Notably the Rde mics promise a GainAssist function to try to keep the audio you're trying to record distinct from any background noise. The extreme dynamic range offered by this audio recording format lets you freely capture audio at essentially any audio volume level.
24-bit audio is the industry standard for post-production workflows and final deliverables. You will need to re-map 32-bit float audio back into a 24-bit fixed point space at some stage of post-production.
If you've recorded audio tracks with moments of super-loud sounds and simply convert that straight to 24-bit, you'll probably end up with clipped, distorted audio. You'll need to fine-tune the levels after capture to ensure they've been adjusted to within the limits of the 24-bit audio format, just as you would ultimately have to choose which highlights and black tones to retain in a Raw photograph to preserve the details ahead of printing, even if you'd captured an absolutely vast dynamic range when you took the photo.
Is this the ultimate in audio for professionals? Well, seeing how Hollywood productions have dedicated audio engineers on-set, probably no. That said, it can be a big help for smaller production teams, independent filmmakers, live event filming scenarios or single-person video creators where it is difficult to monitor audio levels all the time. Having the flexibility of 32-bit float audio to recover sounds that are too loud or too quiet in post-production can be a lifesaver.
hello,
I would say the question is why 32bit float and not 32bit integer? Well, the answer may be that the 32bit float (assuming IEEE 754 float) can hold more values than a 32bit integer but at the expense of precision.. To be more precise, a 32bit float is as precise as a 24bit integer and then the precision diminishes gradually. An easy way to see this is on this site -754-floating-point .. There, on the top field "decimal" one can put 16 777 216 and start increasing that number while observing the fields below..
So, the way I see it is that, bottom line is that one should still prepare the mic in a proper way, because as we move away from the "sweet spot" there goes precision in DBs in the outer regions
I have a Zoom F6 and I love it- 32bit float recording is the future, although it doesn't mean you shouldn't preview/monitor the audio you're going to record. There is the possibility that the microphone itself might not be capable to handle the SPL of the source that you're trying to record- for example, if you're trying to record a trumpet player or a drum and bugle corp and you have a very sensitive microphone, you may need to engage a pad on the mic itself- or if you're close miking a very loud source, you may be clipping the preamp itself. While some may think 32 bit float is a marketing ploy, I disagree- it's an incredible leap forward in recording, but it doesn't mean you shouldn't check your levels first and make adjustments to get the levels you need, what 32 bit float does when used properly is save you from unexpected peaks that would normally have been clipped. I like to think of it as a safety net.
One thing to consider is that these "32-bit" are only applicable to the analog-digital (AD) conversion of an analog signal. Now, if you have a bad analog signal, i.e. if you have a very bad preamp introducing tons of harmonic distortion and a bad microphone that has a very unfavourable frequency-response-profile, then even the best AD-conversion of the universe will not magically turn this into good audio.
So, while some companies are marketing their 32-bit floating conversion process, it would be just as important to know the quality of the mic and preamp used in these audio recorders. It might be better to have a traditional 24 bit device with great preamp/mic stage than the latest ultra-32-bit device with a built-in mic that eats up the transients and that rumbles as hell.
As I understand it, no analog audio amplifier has anywhere near the usable dynamic range to usefully ("usefully" meaning to not just slice up the analog signal magnitude into pointlessly small values) support "32 bit float" audio. What's the catch?
Just read the explanation at the link. However, it doesn't talk about how you combine these two signals digitally without introducing artifacts (due to the fact that you are combining two different audio paths into one). I suspect the same would go for the D/A side. Is this technology considered capable of "high fidelity"? or is it more there is a tradeoff between fidelity and the benefits of the extreme dynamic range?
Storage is cheap, thus it is best to record in the highest quality that is practical for the amount of storage you have on hand. You can always reduce the size and quality later on, and with the right scripts, you can easily automate the compression if you need it.
The issue is that with INT schemes, brighter/louder (call them "HI") parts of the image/sound use most of the bits, and so tiny gradations can be reasonably recorded, but darker/quieter ("LO") parts only use a few bits. This is why pulling details from deep shadow (LO) results in grainy mess, same thing with digital recordings.
Imagine if you could use the same number of bits to record both HI and LO signals, so both are at full precision: now you'd have no issue with "noise" in the LO parts. All you need is a separate number for overall gain.
Integer bit range has a sharp cutoff at 0 dBu, whereas 32F bit audio has no arbitrary clipping point. Instead, the audio input is limited by the maximum input of the analog preamp, which is typically +24 dB in professional equipment.
A condenser microphone typically requires 25 to 40 dB of gain to keep peaks under 0 dBu. In order to keep the peak recording level below 0 dBu (at 24 bit depth), audio is generally recorded to peak at -20 to - 12 dBu, hoping that there will be few if any "surprises" which exceed 0 dBu.
With 32F bit depth, "surprises" have little effect unless they exceed the input capacity, or any limits placed on that input (e.g., a limiter). In practice, it is advisable to stick to the time-honored formula, adjusting peaks to -12 dBu or less.
Another advantage of 32F processing (64F in Pro Tools and Nuendo) is that additive peaks from multiple channels while mixing can be safely ignored. Every doubling of voltage adds 6 dB to the sum. Floating point processing simplifies the mixing process. One can mix to taste then normalize the output to stay within integer 16 or 24 bits, without the need to normalize the sum before processing. The mixed sound is still subject to low level quantization noise, masked by dithering.
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