25

A WAV file has the potential to hold "more" or "better" data than an mp3. WAVs employ no compression, no loss; they are as close to an exact replica as it is possible to get. An mp3 employs lossy compression to achieve the smaller data size. Lossy compression means that information is actually just thrown away if the algorithm decides no-one would be able ...


10

Very good question. I found nothing about it in the manuals. It seems I'm missing some knowledge that the creators of FM8 and Ableton's Operator share and use. So, my question is how do synth makers control the modulator amplitude and how does the interface of the synth and the controls from 0 to 100 change the modulator amplitude in the background? You ...


8

Using a higher order filter will give you a greater roll-off slope in the filters stop-band. So a 1st order filter has a roll-off slope of -6db/octave, 2nd order filter has a roll-off slope of -12db/octave, 3rd order filter has a roll-off slope of -18db/octave, 4th order filter has a roll-off slope of -24db/octave, etc. This means the filter does not act ...


8

No. When you convert a file from .mp3 to .wav, no new information is added: there is no way to regenerate the information that was lost when you created the mp3. All the extra data in the .wav file is redundant.


7

There are three parameters of this filter that are described in the phrase "100 Hz 12 dB per octave low pass filter". I'll cover them in reverse order. Low pass filter - This means the filter does not change lower frequencies ("passes" those frequencies through) and blocks higher frequencies. Sometimes these filters are called "high cut filters", but that ...


6

If you zoom in to your waveform, you will see that it crosses the zero line twice per cycle (880 times per second). If you end your tone recording exactly at a "zero-crossing" then there will be nothing to create a "click" when played back. The "click" comes from ending the waveform somewhere above (or below) the zero-crossing. If the recording ends mid-...


5

-- edit -- this question piqued my curiousity enough that I ran a test for the tonebenders podcast. Check out the results here: https://soundcloud.com/tonebenders-podcast/017-tonebenders-listener-questions-mic-matching-with-izotopes-ozone -- edi t-- I honestly think this is a good question that's worthy of a little thoughtfulness. IMO it is possible to eq ...


5

I think you've misunderstood what Frequency is, with respect to audio. Whilst 'Frequency' typically is 'how frequently something occurs', in audio it's how many times a sine-wave oscillates in a second, rather than how many things you hear in a second. eg. A standard kick-drum track at 60 BPM means you'll hear a kick-drum sound once-per-second. That actual ...


5

MP3 is the 'colloquial' name for "MPEG 1 Layer 3" audio encoding. The purpose of mp3 encoding is to reduce the overall size of an audio data stream whilst maintaining an acceptable level of listening quality. It is implemented using a "codec", meaning that you need an "Encoding" function and a "Decoding" function in order to listen to the audio. The ...


4

FM8 mirrors the DX7 implementation which uses a 0-99 value to represent modulation index of 0 to 14. So, an output level of '85' corresponds to an index of 4.


4

There are definitely tendencies - and these mainly appear through the use of the same types of instruments in a genre, some more explicit than others, e.g. Drum and bass, Funk and A capella. Almost all modern electronic dance music uses a steady repeating kick drum and bass pattern - and as you note, this defines a good portion of the frequency ...


4

It's a Logarithmic scale & is used where a linear scale wouldn't really make sense & would reduce the detail in the lower portions of the graph. As each octave doubles the frequency. The difference between, say, 50Hz & 100Hz is an octave, so is the difference between 5kHz & 10kHz. If that information were to be presented on a linear scale,...


4

In order to make sound, your computer must drive the speaker with a time-varying voltage. In order to create the time-varying voltage, the computer must send a sequence of numbers to a Digital-to-Analog Converter (DAC). The simplest .wav file just contains a sequence of numbers that are ready to send to the DAC. An .mp3 file is a much more sophisticated ...


3

Do you mean in livesound situations? If so, it depends on soo many factors that it is impossible to give a average frequency range. But something i noticed when working with a band that only use in-ears is that feedback through FoH started (if at all) around the lower midrange. I think this is common due to the way lower frequencies radiate. With the band i ...


3

Those combined EQ + spectroscopes can seem a bit misleading. The curve on your EQ isn't always what's actually happening, and similarly metering is only an averaging of the signal because audio is a much faster rate than your monitor. With a regular eq it's really more about using your ears to find something that works. You might be better off using an FFT ...


3

It is true that the sensitivity of our ears varies based on frequency and that high pressure sound can be more damaging without being noticed, but if you are not listening too loud it shouldn't be a problem. You just need to be really careful that it isn't actually too loud. It is possible to damage your hearing without feeling any pain when you are using ...


3

You are applying a low pass filter - this tends to remove the middle frequencies in the spectrum a bit and the upper frequencies a lot. This is how I hear it anyway - try using a simple tone control to simulate the effect - probably just a fair amount of treble cut would do the same. If you want to be really precise use a graphic equalizer that has a bypass ...


3

Change is typically "disturbing". A sharp change of amplitude (a crash, a scream, an explosive sound, etc.) Or even sudden quiet after moderate but steady background noise will disturb some people. So a circuit that detects any sharp change (up or down) in sound amplitude. That would be my primary focus for detection of "disturbing sound". Of course, ...


3

By far most passive acoustic systems are linear and time invariant. As such, they don't create frequencies not present in the original signal. Passive systems that aren't linear are typically of the snaring/clacking variety. They either create overtones to existing frequencies, or they have their own strong resonance but are triggered by external signals. ...


3

Wavelength is the inverse of frequency (1/f) so all you need is to perform an FFT (Fast Fourier Transform) on your signal to get its spectrum (harmonic content). This can be done in many ways but from the way the question is formed ("Is there any way to extract wavelength ranges out of it? I only need to know the numbers."), I suspect Matlab or Scilab might ...


3

Frequencies are a spectrum from 0Hz up to approximately 20kHz. To obtain spectra of sound samples, you will need an implementation of an FFT (Fast Fourier Transform) library. For the application you are describing, you will need to use something like Matlab or Octave.


3

One reason may be there is a need for them besides the use for human listening. Perhaps a human may want to study or devote their careers to Animal audiology. If you want to study an animal that has the ability to hear frequencies above or below what humans can hear then you may want a driver capable of producing frequencies in the range that the ...


2

. but that's just a guess, really.


2

This was a question asked in a Digital Sound and Music exam which has been copy-pasted here (even the "ex-pressed" has been left intact). The question only gives two marks. I think this is the answer: f(t) = Amplitude * sin(2 * π * Frequency * t) So in this case the Frequency would be replaced with 500.


2

for 1/3 octave steps, multiply the previous band by 2^(1/3) (that's 2 to the power of 1/3 = 1.259921049895). Starting with 20Hz, you'll get 20,25.198,31.748,40,50.397,etc, up to 20480. The 'standard' frequency bands for a 1/3 octave (20,25,31.5,40,50,63,etc) are essentially just for labelling - any practical application would use the calculated ...


2

As someone who comes from a sound company, the only way you can be sure that it would negatively effect the headset or headphones in said question is whether it would pass the specification of the speaker or subwoofer in the headphones. Depending on its use and how frequently you push it past it's limit (Mild distortion or blurred sound) is the point where ...


2

This is not possible by traditional, analogue means. As said by Bit Depth, such filters have a property called the order. What that means: the response of a filter of order n can be written as               ( an ⋅ ωn + an-1 ⋅ ωn-1 + ... + a2 ⋅ ω2 + a1 ⋅ ω + a0 ) A(ω) =  ———————————————————————               ( bn ⋅ ωn + bn-1 ⋅ ωn-1 + ... + b2 ⋅ ω2 + b1 ⋅ ω +...


2

In the case where your two audio signals S1[n] and S2[n] are of same length, and we are speaking of discrete time, discrete value signals, the DFT being a linear transform : DFT (S1[n] - S2[n]) = DFT(S1[n]) - DFT(S2[n]) It means that subtracting the spectrum of S2[n] from the spectrum of S1[n] and transform back into time domain signal will produce the ...


2

Let's use some simpler numbers to illustrate the problem. Let's say the smallest string on a piano is 1m, and has a frequency of 200hz (it's a piano for giants). And let's say the lowest note on a piano is 100hz (only one octave because our giants have a narrow hearing range). Given all other factors are consistent (tension, thickness, etc...), we know ...


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