Speaker 1: Get in touch with technology with tech Stuff from how
Speaker 1: stuff works dot com. Hey there, everyone, this is Jonathan
Speaker 1: Strickling with tech Stuff, and today we're gonna tackle a
Speaker 1: subject that I've talked about in the past. Actually, way
Speaker 1: back in two thousand and eight, back when you were
Speaker 1: a knee high to a grasshopper, Chris Pollette and I
Speaker 1: did an episode called how MB three files Work, and
Speaker 1: we talked about the lossy file format, and we actually
Speaker 1: revisited it in two thousand eleven we did an episode
Speaker 1: about the iPod and about MP three players, but I
Speaker 1: really thought it would be a good idea to revisit
Speaker 1: MP three files, MP three players, digital audio in general,
Speaker 1: the difference between digital audio and analog and all of
Speaker 1: that history. Uh, to really give a deep dive, because
Speaker 1: back in those days we did really short episodes and
Speaker 1: so we weren't able to give it the full coverage
Speaker 1: that I think get deserved. Um and we actually reached
Speaker 1: a point in history that I did not anticipate. And
Speaker 1: I am, of course talking about the day when I said,
Speaker 1: you know what, I don't need to carry a smartphone
Speaker 1: and an MP three player. I held out for a
Speaker 1: really long time. You guys who have been long time
Speaker 1: listeners of tech stuff might remember that I really liked
Speaker 1: dedicated devices, Like I really liked having a digital camera,
Speaker 1: and I really liked having an MP three player, and
Speaker 1: I really liked having a phone that was a phone.
Speaker 1: And now I'm like, no, I'm good with just one
Speaker 1: device doing all that kind of thing. So, uh, since
Speaker 1: we've reached that point, the point where our machines are
Speaker 1: sophisticate enough to either have enough storage space to carry
Speaker 1: an impressive music collection, or more likely as the things
Speaker 1: as things have changed these days, um access to a
Speaker 1: streaming service where I don't even have stuff stored permanently
Speaker 1: or like in any any you know, lasting format on
Speaker 1: the phone itself. Instead, I'm streaming a file over the
Speaker 1: Internet to listen to. Dynamically, I thought, why not talk
Speaker 1: about the MP three because who knows, in a few
Speaker 1: years and that might just be a distant memory. So
Speaker 1: this is going to be the first of a three
Speaker 1: part series, and I want to let you guys know,
Speaker 1: I'm not going to record all of these and publish
Speaker 1: them all one right after the other. So it's not
Speaker 1: gonna be MP three Part one, Part two, Part three
Speaker 1: in a row. Uh. In this episode, we're gonna look
Speaker 1: at how digital audio works in general and how it's
Speaker 1: different from analog audio. Uh, and we're also gonna talk
Speaker 1: about how the MP three was created and what it does.
Speaker 1: In the next episode, I'm gonna take a deeper dive
Speaker 1: into how an MP three file works, how it compresses audio.
Speaker 1: It gets really technical. And in the final episode of
Speaker 1: the series, we're gonna explore the history of the MP
Speaker 1: three player and how Apple ended up dominating that space
Speaker 1: for so long, to the point that we have things
Speaker 1: called podcasts. But don't worry, I have other episodes to
Speaker 1: divide up this content. So, like I said, it's not
Speaker 1: all gonna be in a row. I don't want you
Speaker 1: to have a month of MP three related episodes, but
Speaker 1: you know, every couple of episodes, expect one of these.
Speaker 1: It's kind of an interesting subject, I think. So to
Speaker 1: start it all off, we all have to take a
Speaker 1: quick trip to Germany. So anyone who is not in
Speaker 1: Germany get your passport. I was actually in Germany not
Speaker 1: that long ago. I got to visit Berlin and had
Speaker 1: a wonderful time. And in Germany there's a company called
Speaker 1: frown Hoffer Gazelle Shoft and you might wonder, well, what
Speaker 1: does this company do? They think I joke that my profession,
Speaker 1: that my title that I should put on my business
Speaker 1: card it should say professional smart person. And well, no joke,
Speaker 1: that's what these people are. They they specialize in research
Speaker 1: and development, applied research. It's a whole company that specializes
Speaker 1: and applied research. And it's huge. It encompasses sixties seven
Speaker 1: institutes and research units across Germany. Well back in the
Speaker 1: eighties and there was a researcher named Karl Heinz Brandenburg,
Speaker 1: and Karl Heinz made a breakthrough round seven uh and
Speaker 1: came up with this clever idea about encoding audio. He
Speaker 1: was actually working towards creating a way that would allow
Speaker 1: for high audio quality transfer but having a low bit
Speaker 1: rate sampling so that file sizes and transfer times wouldn't
Speaker 1: get out of control. Because you got to remember, this
Speaker 1: is the eighties, this is before the Worldwide Web was
Speaker 1: a thing that would That wouldn't happen until the early nineties,
Speaker 1: so the Internet is very young. In fact, they weren't
Speaker 1: even looking at the Internet as a method of distribution
Speaker 1: for this particular type of encoded audio. They were looking
Speaker 1: at using this to transmit across telephone lines, so they
Speaker 1: need to have something that was going to be high
Speaker 1: quality but low space. So what the heck does that mean?
Speaker 1: All right, Well, digital audio and analog audio are very
Speaker 1: different things. So to understand that, we need to look
Speaker 1: at how sound works and how we describe sound, because
Speaker 1: that informs how we can capture sound and replicate those
Speaker 1: qualities digitally. So stick with me. We're gonna go back
Speaker 1: to school for some basic sound science. And this goes
Speaker 1: back to the way sound physically moves through a medium,
Speaker 1: whether that's a solid or through the air or through water.
Speaker 1: Sound is vibration. Now we sense this primarily through hearing
Speaker 1: it or some type feeling it. If it's the right
Speaker 1: frequency in the right amplitude, we can actually feel sound.
Speaker 1: Anyone who stood close to, say a sub wiffer that
Speaker 1: was really blasting out bass notes, you know what I'm
Speaker 1: talking about, You can feel it pressing against you. Well,
Speaker 1: sound travels through the air when molecules vibrate against each other,
Speaker 1: and this creates instances of increased pressure and decreased pressure
Speaker 1: at what is a hyperlocal level. We're not talking about
Speaker 1: weather maps here, We're talking about tiny, little areas. So
Speaker 1: this increase and decrease in pressure is something that we
Speaker 1: can sense as sound. When those changes in pressure affect
Speaker 1: a diaphragm, such as one that's in a microphone or
Speaker 1: maybe your ear drum, for example, it causes the diaphragm
Speaker 1: to actually move. So increased pressure pushes the diaphragm in,
Speaker 1: and decreased pressure doesn't really pull the diaphragm out. I mean,
Speaker 1: you could say it it pulls the diaphragm out, but
Speaker 1: to be more accurate, the diagram actually pushes outward because
Speaker 1: the pressure on the outside is lower than the pressure
Speaker 1: on the inside. But you get what I'm saying. The
Speaker 1: diaphragm begins to to flex inward and outward depending upon
Speaker 1: the amount of pressure that it's it's encountering. You could
Speaker 1: imagine this being kind of like a drum drum, not
Speaker 1: an ear drum, but an actual drum and striking it.
Speaker 1: That's the same sort of thing. So sound is the
Speaker 1: fluctuations of pressure, which we can diagram as a wave
Speaker 1: or a wave length a wave form on an X
Speaker 1: Y axis, So the horizontal line that access that represents
Speaker 1: time that has passed, and the vertical axis represents the
Speaker 1: amplitude or the volume of the sound wave. The wave
Speaker 1: length of the sound, which is the distance between successive
Speaker 1: points on a wave, such as like the successive crests
Speaker 1: on a wave. That tells you a lot about the frequency.
Speaker 1: So sound moves at a constant rate through a given medium,
Speaker 1: but it moves at different rates through different media. So,
Speaker 1: in other words, it moves at different speed through a
Speaker 1: solid than it does through air. If the crests of
Speaker 1: each sound wave are really close together, that's a high
Speaker 1: frequency sound. More waves will pass through an arbitrary point
Speaker 1: within a second than waves that are spaced further apart.
Speaker 1: That would be a lower frequency sound. Higher frequency sounds
Speaker 1: have a higher pitch than lower frequency sounds. So if
Speaker 1: you hold a single note at a constant frequency, you'll
Speaker 1: have what is called a simple harmonic motion. That means
Speaker 1: the vibrations are moving at a constant rate inward and outward.
Speaker 1: The cycle is constant. A tuning fork is a good
Speaker 1: example of this. So if you hear a clear C
Speaker 1: note played on a musical instrument, that could be a
Speaker 1: simple harmonic motion. It won't be, but it could be.
Speaker 1: I'll tell you why it won't be in a minute.
Speaker 1: So the frequency of vibration doesn't change, and so you
Speaker 1: would get this very clear note as a result, And
Speaker 1: if you were to diagram it, you would have very
Speaker 1: regular crests and troughs, all of the same amplitude and
Speaker 1: distance from each other. The frequency and volume would remain constant,
Speaker 1: assuming of course, that you're not trying to change the
Speaker 1: frequency or volume. Now, this is where I point out
Speaker 1: most musical instruments don't produce a single clear note, even
Speaker 1: if played expertly. They actually create several resonant frequencies. So
Speaker 1: every physical object resonates at several different frequencies. You've probably
Speaker 1: seen this in various programs. MythBusters did one about bridges,
Speaker 1: the idea being that if you were to have a
Speaker 1: group of people marching on a bridge at the bridge's
Speaker 1: resonant frequency, it could cause the bridge to start to
Speaker 1: vibrate and swing out of control. Well, there's a reason
Speaker 1: for this. You may have also seen videos of people
Speaker 1: singing a certain note and causing a crystal glass to shatter.
Speaker 1: That's because that crystal glass does have a resonant frequency,
Speaker 1: and if you can hit that resonant frequency at the
Speaker 1: right volume, you can cause the glass to start to deform,
Speaker 1: or the crystal in this case, to deform to a
Speaker 1: point where it loses integrity and it shatters as a result. Well,
Speaker 1: the resonation of an object is dependent upon lots of
Speaker 1: different factors, and in fact, most stuff will resonate at
Speaker 1: different frequencies but at different intensities. Like there might be
Speaker 1: one sweet spot, one specific frequency that will have the
Speaker 1: greatest effect, but other related frequencies may also have an effect.
Speaker 1: It will just be to a lesser extent. Well, if
Speaker 1: you were to pluck a guitar string, just you've tuned
Speaker 1: it to whatever note doesn't matter. Let's say it's you've
Speaker 1: tuned it to to G and you play the G
Speaker 1: string on your guitar. Uh, the note that you will
Speaker 1: hear really over all others will be g that that
Speaker 1: is going to be the one that will sound the loudest,
Speaker 1: But it will also play resonant frequencies at a decreased amplitude,
Speaker 1: in other words, of decreased volume, so you still hear
Speaker 1: the intended note above everything else, above all the other
Speaker 1: resonant frequencies. This is called a complex tone, and that
Speaker 1: collection of frequencies in their amplitudes is called the spectrum
Speaker 1: of sound. You get a full spectrum. Now, some of
Speaker 1: the components of that complex tone will be uh imperceptible
Speaker 1: to you. You there'll be so quiet that you wouldn't
Speaker 1: really notice them. They might affect the overall quality of
Speaker 1: the sound, but in such a subtle way that it
Speaker 1: may be difficult for you to even put it into words.
Speaker 1: Each of those little components is called a partial. So
Speaker 1: in the example of a guitar string, the partials are
Speaker 1: all integers of the same fundamental frequency, and the sound
Speaker 1: has a harmonic spectrum. But as you get further away
Speaker 1: from that fundamental frequency, the amplitude decreases significantly. So, like
Speaker 1: I said, you get far enough away, they are technically there,
Speaker 1: but they might be imperceptible to you. Now, some sounds
Speaker 1: have frequencies that aren't integers of a fundamental frequency and
Speaker 1: are inharmonic uh. Certain bells, Like if you hear a
Speaker 1: bell ring, you can probably pick out a couple of
Speaker 1: different frequencies there that are not harmonic frequencies. These are
Speaker 1: very complex sounds, and to our perception, if it's complex enough,
Speaker 1: it can seem like there's no single discernible pitch. They're
Speaker 1: like there's no fundamental frequency over all the others. If
Speaker 1: it's complex enough, we call it noise. That is the
Speaker 1: technical term. It is noise. Now, the unit we use
Speaker 1: to measure frequency is the hurts uh H, E R
Speaker 1: t Z. Typical human hearing ranges from twenty hurts, which
Speaker 1: means a wave will pass a given arbitrary point twenty
Speaker 1: times within a second, all the way up to twenty
Speaker 1: killer hurts, which means a wave will pass a particular
Speaker 1: point in time twenty thousand times in a second, or
Speaker 1: particular point on your wave form twenty thousand times in
Speaker 1: the second. And most of our sensitivity tends to be
Speaker 1: between one or two killer hurts up to four or
Speaker 1: five killer hurts. That's generally where we have human voices,
Speaker 1: and we've really gotten good at picking those out of
Speaker 1: over everything else. So our sensitivity of hearing is really
Speaker 1: concentrated between one killer hurts and four killer hurts or
Speaker 1: two and five depending upon whom you ask. Now we
Speaker 1: get back over to amplitude. That is referring to the
Speaker 1: height of the wave. It also refers to the volume
Speaker 1: the loudness of something. Amplitude means bigness, So how big
Speaker 1: is the sound? Well, the greater the amplitude, the louder
Speaker 1: it is, and amplitudes can have an enormous range and
Speaker 1: affect how we perceive sounds. So, for example, take a
Speaker 1: really complicated classical piece of music. It's just easy to
Speaker 1: explain it in that term. You might have a wretch
Speaker 1: in that classical piece of music in which all the
Speaker 1: instruments are more or less playing at a similar volume,
Speaker 1: so the sound from each instrument section has a similar amplitude.
Speaker 1: But then there might be one segment where an instrument
Speaker 1: group or maybe even a single soloist has an increased
Speaker 1: amplitude and increased volume. It rises over the rest of
Speaker 1: the orchestra, and that peak of the amplitude is called
Speaker 1: the attack of the sound, and the entire range of
Speaker 1: amplitudes is called the amplitude envelope. Now this is important
Speaker 1: when we get to m P three's because the way
Speaker 1: we perceive these sounds, uh that that has everything to
Speaker 1: do with the way the MP three was designed. The
Speaker 1: whole point of the MP three was to try and
Speaker 1: create a small file size to represent what we can
Speaker 1: hear and kind of ignore everything else. But we'll get
Speaker 1: to that in a little bit more more time so
Speaker 1: this is really interesting to me. If you take a
Speaker 1: sound and you double its amplitude, you increase the amplitude
Speaker 1: by twofold, a listener would not necessarily feel that the
Speaker 1: sound is twice as loud. Human hearing is incredibly subjective,
Speaker 1: and typically for most listeners, it would require much more
Speaker 1: than doubling the sounds amplitude for them to feel that
Speaker 1: the sound itself was twice as loud. This perception of
Speaker 1: volume is important when we get to the lossy formats
Speaker 1: for audio files. Now I've given you all this information,
Speaker 1: and I know everyone is probably thinking, you know, I
Speaker 1: learned this in primary school, elementary school. All of this
Speaker 1: is really familiar to me, and you're maybe rolling your
Speaker 1: eyes because it's so basic. But I think it's important
Speaker 1: to have that refresher so that you can understand the
Speaker 1: difference between sound as we experience it and sound as
Speaker 1: the way we hold it digitally and replicate it digitally.
Speaker 1: For one thing, this illustrates how sound in the real
Speaker 1: world is a continuum. It's a continuum both in frequency
Speaker 1: and amplitude. You can have sound changing in frequency very
Speaker 1: smoothly from one pitch to another. You can also have
Speaker 1: sound increase or decrease in amplitude in a very smooth way.
Speaker 1: And it is continuous, it's unbroken, it can have smooth transitions.
Speaker 1: And these qualities provide challenges when we want to describe
Speaker 1: something digitally, because at the heart of digital information is
Speaker 1: the bit, the basic unit of information. It is a
Speaker 1: unit of information that only has two states zero or
Speaker 1: one is essentially off or on. When you get down
Speaker 1: to defining information in just two states, then you start
Speaker 1: to look at something that's continuous and you realize this
Speaker 1: is going to be a challenge. How do I describe
Speaker 1: a continuous experience in very discreet amounts of information. And
Speaker 1: that's when we get to the methodology we've developed to
Speaker 1: digitally encode sound. I'm going to get into that in
Speaker 1: just a minute, but before I do that, let's take
Speaker 1: a quick break to thank our sponsor. All right, let's
Speaker 1: get back into it. So we've talked about the nature
Speaker 1: of sound. Analog sound, by the way, tries to replicate
Speaker 1: exactly what we would experience in nature. It tries to
Speaker 1: create this continuous experience, so you get these smooth waves
Speaker 1: of frequencies and amplitudes. And that's why some people argue
Speaker 1: that that analog styles of of sound recordings are superior
Speaker 1: to digital ones. I don't necessarily think they're right, but
Speaker 1: they often feel that way. So something like a vinyl album,
Speaker 1: which is an analog format of digital or sorry, an
Speaker 1: analog format of music storage I should say sound storage. Uh,
Speaker 1: they think that that is superior to say a CD,
Speaker 1: which is a digital storage format. Uh. And who's to say.
Speaker 1: I mean, like, if your sense of hearing is incredibly
Speaker 1: well tuned, you might be able to pick up on
Speaker 1: some differences. Or if someone did a really terrible job
Speaker 1: encoding music digitally, then that might reveal itself to you
Speaker 1: as well. Uh. But this is one of those things
Speaker 1: that I think a lot of people feel they can
Speaker 1: tell the difference, but if they would do a double
Speaker 1: blind test, they might be surprised at how difficult it is.
Speaker 1: If things if everything's working the way it should, then
Speaker 1: there shouldn't be a perceptible difference at any rate. Digital
Speaker 1: audio has two really important factors, sample rate and bit depth,
Speaker 1: or to another extent, bit rate. We'll talk about bit
Speaker 1: rate as well. So the sample rate refers to how
Speaker 1: many times you reference an analog sound to create the
Speaker 1: digital version. So sound like I said, is uninterrupted. In
Speaker 1: the analog world, you've got that that nice wave form.
Speaker 1: In the analog world, that's not how digital world works.
Speaker 1: Digital world, we have to describe that sound in a
Speaker 1: series of discrete snippets of sound. It's probably easiest to
Speaker 1: describe this with an analogy to movies on film. If
Speaker 1: you work with film, like you're creating a movie on film,
Speaker 1: then you know that you're not looking at a real
Speaker 1: moving picture when you see the film played out at
Speaker 1: the cinema. Instead, what you're looking at is a series
Speaker 1: of photographs. If you take a film strip and you
Speaker 1: look at it under a light, you'll see it's one
Speaker 1: after another photograph. It's just a series of pictures. It's
Speaker 1: only when you play them back at the right speed
Speaker 1: and you projected onto a screen that you get the
Speaker 1: illusion of continuous motion. But it's not really continuous. It's
Speaker 1: just this series of photographs played at twenty four frames
Speaker 1: per second in the case of actual film. So that
Speaker 1: ends up being very analogous to the way we encode
Speaker 1: digital audio. You take the analog recording and you take
Speaker 1: snapshots of sound. The more frequently you take those snapshots,
Speaker 1: the higher your sample rates. So in other words, if
Speaker 1: you did one a second, your sample rate would be awful.
Speaker 1: You would have a sample rate of one. But the
Speaker 1: higher the sample rate, the close to your digital representation
Speaker 1: will be to the frequency in the analog sound format. Actually,
Speaker 1: what's really important to remember is that your sample rate
Speaker 1: has to be about twice actually does have to be
Speaker 1: twice what the highest frequency sound is in your recording.
Speaker 1: It has to be because if it's not, it cannot
Speaker 1: encode that sound accurately. It's kind of interesting and you
Speaker 1: might wonder, how do we take these snapshots in the
Speaker 1: first place. Well, if you're capturing audio, let's say we're
Speaker 1: recording to digital, So we've got a microphone set up,
Speaker 1: and we're recording to a digital media storage. Like let's
Speaker 1: just say we're recording straight to someone's hard drive. So
Speaker 1: we're talking into a microphone recording to a hard drive.
Speaker 1: So you're using an analog microphone. Let's say you would
Speaker 1: need an analog to digital converter. Now, this particular component
Speaker 1: can receive discrete voltages from another device like your microphone.
Speaker 1: So your microphone is converting sound into uh differences in voltage.
Speaker 1: That's essentially how it communicates. So that it can then
Speaker 1: send that to some other element. In this case, it's
Speaker 1: sending it to the the analog to digital converter so
Speaker 1: that it can be stored digitally on your hard drive.
Speaker 1: So this analog digital converters references or samples the discrete
Speaker 1: voltage many times every second in order to create a
Speaker 1: digital representation of the analog sound. It converts the voltages
Speaker 1: into numbers in a process called quantization, and we express
Speaker 1: those numbers in bits, So these are zeros and ones.
Speaker 1: When you want to play the digital audio, a digital
Speaker 1: to analog converter does the same process in reverse. So
Speaker 1: it takes this digital information, these zeros and ones and
Speaker 1: converts it into a series of discrete voltages, which then
Speaker 1: can be amplified and sent to a speaker and create sound.
Speaker 1: So all of that's really important. But now let's let's
Speaker 1: talk about some concrete examples. And the best way to
Speaker 1: do this is to go with compact discs. Because we
Speaker 1: have a standard sample rate for compact discs, and that
Speaker 1: standard sample rate is forty four point one killer hurts
Speaker 1: to create CD equality audio. That means that the audio
Speaker 1: is sampled forty four thousand, one hundred times every second
Speaker 1: the way to hear. You say, the range of human
Speaker 1: hearing you said only goes to twenty hurts to twenty
Speaker 1: killer hurts. If it only goes up to twenty killer hurts,
Speaker 1: why are you sampling at forty four thousand, one hundred
Speaker 1: times every second? If it's twenty thousand times a second
Speaker 1: for the frequency, why go up to forty four thousand,
Speaker 1: one hundred Is there some relationship between that and the
Speaker 1: CD sample rate? And the answer is yes. So there
Speaker 1: is a theorem called the Niquist Shannon sampling theorem, and
Speaker 1: that states that the sample rate must be twice the
Speaker 1: maximum frequency of a recording in order to describe the
Speaker 1: frequency properly. So the general thought is the maximum frequency
Speaker 1: most humans can here's twenty killer hurts. And for that reason,
Speaker 1: Phillips and Sony when they were working to create the
Speaker 1: CD format to make it a standard, they decided on
Speaker 1: forty four point one killer hurts as that standard sample
Speaker 1: rate for c D audio. It was more than double
Speaker 1: the top frequency generally considered to be in the upper
Speaker 1: level of human hearing. But what happens if you were
Speaker 1: to lower the sampling rate. What if you didn't sample
Speaker 1: at What if you sampled at let's say sixteen killer hurts,
Speaker 1: so sixteen thousand times a second you sample it. Well,
Speaker 1: that means you would only be able to record and
Speaker 1: replicate any sound with a frequency up to eight killer
Speaker 1: hurts or less, so eight thousand hurts or less. But
Speaker 1: if you had any sound that was greater than eight
Speaker 1: thousand hurts or eight killer hurts, anything higher than that,
Speaker 1: it would be folded down to fit below the eight
Speaker 1: killer hurts limit. Perceptually, that means the sounds you would
Speaker 1: hear in the playback could include frequencies that were not
Speaker 1: present in the original performance of that sound. So let's
Speaker 1: say that I'm using a sample rate of sixteen uh,
Speaker 1: you know, killer hurts, and someone is playing a musical
Speaker 1: instrument and they play a note that's at a nine
Speaker 1: killer hurts frequency. Well, because I'm sampling at sixteen killer hurts,
Speaker 1: my limit for frequencies is eight killer hurts. If you
Speaker 1: play something at nine killer hurts, what happens is it
Speaker 1: the recording seems to fold the sound back, and it
Speaker 1: folds it back at the same limit that the sound
Speaker 1: goes over. The sample rate, or rather the Nyquist limit,
Speaker 1: I should say, not the sample rateself but the Nyquist limit,
Speaker 1: so nine killer her sound played. My limit is eight
Speaker 1: killer hurts. Well, nine killer hurts is one killer hurts
Speaker 1: more than eight, so it folds it back and the
Speaker 1: sound you would hear on the recording would be seven
Speaker 1: killer hurts. So the original sound is nine killer hurts,
Speaker 1: the playback sound is seven killer hurts, and you would
Speaker 1: hear something recorded that wasn't actually played. That's why you
Speaker 1: have to have a really high sample rate so that
Speaker 1: you don't have these instances where sound gets folded back
Speaker 1: into the frequency range, because otherwise what you are hearing
Speaker 1: is not an accurate representation of what was actually generated
Speaker 1: what you were trying to record. This whole phenomenon, by
Speaker 1: the way, is called fold over or sometimes aliasing. So
Speaker 1: that's sample rate. But then we've got bit depth. Now,
Speaker 1: this is all about measuring the volume or amplitude of
Speaker 1: a sound. So you have a range. You just make
Speaker 1: an arbitrary range to say, like we're gonna go quietest
Speaker 1: to loudest, and you just define what that range is.
Speaker 1: It could literally be any range. Let's say you say
Speaker 1: zero to one hundred. Zero is dead silence, no sound
Speaker 1: at all. One hundred is as loud as the sound
Speaker 1: ever gets. It's the peak volume of sound. That means
Speaker 1: you can describe all the different volumes within that recording
Speaker 1: at a number between zero and one hundred. But let's
Speaker 1: say you take that same recording and instead of making
Speaker 1: the range zero to one hundred, you say it's zero
Speaker 1: to two thousand. You haven't made the volume louder. The
Speaker 1: volume is still the exact same as it was when
Speaker 1: you called the range zero to one hundred. But what
Speaker 1: you have done is added more units. You have created
Speaker 1: more precise steps between absolute silent and as loud as
Speaker 1: it gets. So you've just increased the size of the
Speaker 1: range so that you can be more precise in the
Speaker 1: differences in volume. And this is really important. So let's
Speaker 1: say that you've got a sound that you rank at
Speaker 1: seventy eight and another sound that you rank at seventy nine,
Speaker 1: and that's gonna be the same for both of these ranges. Uh,
Speaker 1: just two different examples. Actually, So you've got your zero
Speaker 1: to one range, and a seventy eight would be seventy
Speaker 1: eight percent of the loudest sound in the entire recording,
Speaker 1: and at seventy nine would be a seventy nine of
Speaker 1: the loudest sound in the entire recording. That's an actually
Speaker 1: pretty hefty jump. But let's say we instead went with
Speaker 1: that zero to two thousand range and you still had
Speaker 1: seventy eight and seventy nine. Well, seventy eight would represent
Speaker 1: three point nine percent of the full volume and seventy
Speaker 1: nine would resent represent three point nine five of a
Speaker 1: full volume. In other words, you'd be able to mark
Speaker 1: much more subtle differences in volume, and that means you
Speaker 1: can have more nuance in your recording. And since we're
Speaker 1: talking about a natural sound to start off with, so
Speaker 1: you're taking a natural sound and you're trying to digitize it.
Speaker 1: Smooth changes in amplitude are possible in natural sound. Using
Speaker 1: a broader range to describe the volume is best if
Speaker 1: you want to get an accurate representation or resolution of
Speaker 1: that sound. Going back to that zero to one range
Speaker 1: changes in volume would be more chunky. Two sounds that
Speaker 1: have slight differences in amplitude would end up being defined
Speaker 1: as being identical because you wouldn't have the precision. You know,
Speaker 1: you couldn't say this one seventy eight and a half.
Speaker 1: It would either be seventy eight or seventy nine. So
Speaker 1: you could have two sounds that in a greater precision
Speaker 1: you could tell the difference between their volumes. But if
Speaker 1: you have that lower, that more shallow bit depth, you
Speaker 1: wouldn't be able to tell the difference of it. You
Speaker 1: would lose that new once that's subtlety. This is part
Speaker 1: of the reason why people say, like a lot of
Speaker 1: the modern music has uh lower ranges and changes in volume,
Speaker 1: like the the loudest loud parts and the softest soft parts.
Speaker 1: That range has decreased over time, which a lot of
Speaker 1: people have argued has meant that music has gotten less
Speaker 1: complex and therefore, in some minds, less interesting. That's on
Speaker 1: a related uh kind of philosophy to what I'm talking
Speaker 1: about here. So you want to have those smaller steps
Speaker 1: between each unit so you can create greater resolution, more
Speaker 1: smoothness to the recorded audio. And it's actually the bit
Speaker 1: rate and CD audio that will help make the sound
Speaker 1: seem smooth. So if you ever listened to eight bit music,
Speaker 1: you know, like the kind from old video game consoles,
Speaker 1: that sound is really harsh and sort of chunky and
Speaker 1: has an appeal, but it's not you know, it's not
Speaker 1: smooth at all. It can create an amazing effect, but
Speaker 1: if you want to represent true analog sound, it's not awesome.
Speaker 1: If you went up to sixteen bit, that's CD quality
Speaker 1: bit depth, it's much better. Uh, Professional recording studios will
Speaker 1: do four bit or thirty two bit because they're gonna
Speaker 1: do a lot of post processing work on those audio files.
Speaker 1: And when you do that post processing work, if you
Speaker 1: do it at sixteen bit, the stuff you're doing, the
Speaker 1: changes you make can become noticeable, and most times you
Speaker 1: don't want that. You don't want it to be you know,
Speaker 1: you don't want it to stand out from the rest
Speaker 1: of the audio file. But that's the only reason they
Speaker 1: go up to twenty four bit or thirty two bit.
Speaker 1: There'd be no point in playing it back at that rate,
Speaker 1: that bit depth, because human hearing is not so adept
Speaker 1: to tell the difference, at least not from most human ends.
Speaker 1: So if you played back a recording at sixteen bit
Speaker 1: and another one at four bit, it's the same piece.
Speaker 1: Most people would not be able to tell the difference
Speaker 1: because you've already reached a resolution that equals the precision
Speaker 1: of human hearing. Keeping in mind again, human hearing is subjective,
Speaker 1: not everyone is equal. There's some people who have incredible
Speaker 1: hearing who may be able to pick out that difference.
Speaker 1: I am not one of those people, but I am
Speaker 1: a person who's going to tell you. We'll get to
Speaker 1: the last section in just a bit, but first let's
Speaker 1: take another quick break to thank our sponsor. All Right,
Speaker 1: So bits depth, what we just talked about that can
Speaker 1: be thought of is how well the sound is described,
Speaker 1: and the sampling rate is how frequently or how much
Speaker 1: the sound is described. And CD Audio quality has sixteen
Speaker 1: bit audio. That means that they actually have sixty five thousand,
Speaker 1: five hundred thirty six different levels of volume that they
Speaker 1: can describe within an audio track. So my example of
Speaker 1: zero to two thousand that is primitive compared to c
Speaker 1: D audio because it has the sixteen bit style five
Speaker 1: hundred thirty six different levels. And how is that possible. Well,
Speaker 1: when we say sixteen bit, remember a bit represents two
Speaker 1: states zero or one. So you take the number two
Speaker 1: and then you raise it to the power of sixteen ah,
Speaker 1: so you multiply to by itself sixteen times and you
Speaker 1: get sixty five thousand, three D fifty six. So that's
Speaker 1: that's where that number comes from. Now, with your digital sample.
Speaker 1: You have a collection of points that roughly replicate the
Speaker 1: shape of an analog sound wave. It's gonna look a
Speaker 1: little funky, but you'll be able to see what the
Speaker 1: frequency and amplitude generally was of the original recording if
Speaker 1: you were to plot this on an X y axis.
Speaker 1: But if you were just to connect each successive point
Speaker 1: with a straight line, even as close together as they
Speaker 1: would be, because you're looking at forty four thousand one
Speaker 1: times a second, it had sound pretty awful. So we
Speaker 1: actually use an algorithm called interpolation to join the points
Speaker 1: smoothly to imitate a sound wave form, and that gives
Speaker 1: a musical playback program the ability to replicate an analog
Speaker 1: wave form. And that's actually called pulse code modulation or
Speaker 1: pc M. And if you store audio uh intact this way,
Speaker 1: you would have what we call a lossless audio file,
Speaker 1: which means exactly what it sounds like. None of that
Speaker 1: data would ever get filtered out of the file, even
Speaker 1: if the sounds were beyond the range of human hearing,
Speaker 1: they would be recorded, and you would have a lossless
Speaker 1: file format. Those files tend to be quite big, depending
Speaker 1: upon how long a recording you make. Of course, all right.
Speaker 1: So now here's where it gets a little confusing. And
Speaker 1: I think I even said bit rate a couple of
Speaker 1: times when I really meant bit depth earlier. But up
Speaker 1: to this point, I really was talking bit depth. So
Speaker 1: my apologies to all of you out there if a
Speaker 1: bit rate slipped through because I did not mean it.
Speaker 1: Now I'm going to talk about bit rate and show
Speaker 1: you how it's different than bit depth. Bit Rate refers
Speaker 1: to the amount of data audio uses per second or
Speaker 1: requires per second of recording, and you derive bit rate
Speaker 1: from the bit depth and this sampling rate it's represented
Speaker 1: as bits per second. So again let's go to seed
Speaker 1: equality sound. That makes it easy. You have thousand samples
Speaker 1: per second, you've got sixteen bits or two bites because
Speaker 1: remember a bite is eight bits, so you two bites
Speaker 1: to describe each sample. So two bites for samples per second.
Speaker 1: Uh plus you probably are gonna have to multiply that
Speaker 1: by two because you're probably recording in stereo, so you
Speaker 1: have to do that once reach track. So you get
Speaker 1: that number, then you have to multiply that by sixty
Speaker 1: seconds to determine how much data per minute you are
Speaker 1: creating when you're recording and with seed quality audio that
Speaker 1: ends up being about ten megabytes of data per minute.
Speaker 1: Now these days that's not really that big a deal
Speaker 1: because we're dealing with super fast Internet speeds and enormous
Speaker 1: hard drives. But just a few years ago, that was
Speaker 1: considered to be a really sizeable file, I mean an
Speaker 1: enormous file. And so if you wanted to find a
Speaker 1: way to distribute digital audio so it didn't take up
Speaker 1: too much space, you had to figure out how you
Speaker 1: could compress those files and make them smaller, make them
Speaker 1: more manageable. And now we can finally get back to
Speaker 1: Germany and Hair Brandenburg. You thought we left him behind,
Speaker 1: We didn't. He was just part of a flashback. So
Speaker 1: let's go to the MP three. First of all, it
Speaker 1: gets its name from the Motion Picture Experts Group, also
Speaker 1: known as IMPEG. It was part of a project that
Speaker 1: IMPEG was doing that was looking at ways of compressing
Speaker 1: audio along with the work that they were doing with
Speaker 1: video files. It's actually named after the process that they developed,
Speaker 1: called IMPEG Audio Layer three. So yes, there was a
Speaker 1: layer one and a layer two. Layer three was a
Speaker 1: refinement of the approach and was the one that was
Speaker 1: actually successful in the market now, Brandenburg was working with
Speaker 1: an instructor he was pursuing. Brandenburg was pursuing a PhD
Speaker 1: at the time and trying to come up with a
Speaker 1: practical means of transmitting digital audio across phone lines, and
Speaker 1: in the process he began to experiment with algorithms that
Speaker 1: could take digital audio information and determine which bits are significant.
Speaker 1: Anything that was deemed insignificant could be discarded. So the
Speaker 1: thinking was that information we cannot perceive as human beings
Speaker 1: is worthless. There's no point in preserving it in an
Speaker 1: audio file format. It's just taking up space that we
Speaker 1: can't even perceive when we play it back, So there's
Speaker 1: no reason to replicate it. There's no reason to record it.
Speaker 1: Leave it out, and that way you could compress digital
Speaker 1: audio files. Or to put it another way, if the
Speaker 1: algorithm determined that a sound was outside the range of
Speaker 1: human hearing, it would drop it from the encoding process,
Speaker 1: so you get a sound file much smaller than the
Speaker 1: more accurate representative version. So the lossless version would be
Speaker 1: more accurate to the original sound. But this new version,
Speaker 1: what we would call a lossy version, a compressed file
Speaker 1: would be able to replicate it pretty well if it's
Speaker 1: designed properly, and it maybe to a point if you
Speaker 1: design it well enough that you couldn't tell the difference
Speaker 1: between the two. Uh. That took some time. That was
Speaker 1: not easy to do. So the new file, the new version,
Speaker 1: the compressed one, the lossy format, would only have the
Speaker 1: actual relevant data, and from that point forward, the challenge
Speaker 1: was to determine what are the benchmarks to figure out
Speaker 1: what is relevant versus what is irrelevant, because if you
Speaker 1: lose too much information, you change the quality of the recording,
Speaker 1: meaning it's no longer an accurate representation of the original sound.
Speaker 1: So you might say that any sound below twenty hurts
Speaker 1: isn't relevant because it's below the range of your typical
Speaker 1: human humans ability to hear. You might say that anything
Speaker 1: above twenty thousand hurts or twenty killer hurts is irrelevant
Speaker 1: because humans typically can't hear sounds above that frequency. You
Speaker 1: might say that sound at a certain amplitude or lower
Speaker 1: are irrelevant because they're so quiet that humans wouldn't hear them.
Speaker 1: Or you might say that if a certain sound is
Speaker 1: at a lower amplitude and a different sound is at
Speaker 1: a higher amplitude, the higher amplitude sound is drowning out
Speaker 1: the lower amplitude sound, and so we humans don't really
Speaker 1: perceive the lower amplitude sound. This is where we get
Speaker 1: into psychoacoustics. It's not just what we hear, but how
Speaker 1: we perceive the sound itself. And a lot of that
Speaker 1: went into formulating the algorithms to figure out how to
Speaker 1: compress this music in a way where you get a
Speaker 1: recording that represents the original without uh, you know, compromising
Speaker 1: too much and still getting the file size to a
Speaker 1: manageable size. And these are the decisions you have to
Speaker 1: make to figure out which bits of information you keep
Speaker 1: in which ones you ditch. Well Brandenburg and a team
Speaker 1: we're working on our fighting this approach in the late
Speaker 1: eighties and early nineties. And he said, at one point
Speaker 1: he thought he had nailed it, and then he heard
Speaker 1: an acapella song, It was Tom's Diner by Suzanne Vega,
Speaker 1: and then he listened to the compressed MP three version
Speaker 1: of that song, using the the version of MP three
Speaker 1: that had been developed up to that point, and he said,
Speaker 1: it ruined the song. It trashed it. It sounded terrible.
Speaker 1: He said that other representations of music seemed fine with
Speaker 1: this particular approach, but when they went with this stripped
Speaker 1: down acapella song with this particular kind of you're in
Speaker 1: the middle of a space, listening to Suzanne Vegas sing,
Speaker 1: it ruined her voice, and so the team began to
Speaker 1: tweet the compression algorithms to correct for this problem, and
Speaker 1: it took a lot of work to figure out, Okay, well,
Speaker 1: what are the elements of sound that we messed with
Speaker 1: that have created this issue, and ultimately they were finally
Speaker 1: able to create an MP three file that didn't distort
Speaker 1: or ruin the recording. Brandberg said he listened to that
Speaker 1: song somewhere between five hundred and a thousand times, and
Speaker 1: then he saw Suzanne Vega performance live and he was
Speaker 1: able to recognize all of those subtle changes in her
Speaker 1: voice because he had paid so close attention to it
Speaker 1: during the process of tweaking this algorithm. He said, Ultimately,
Speaker 1: the real telling thing is he still enjoyed the song,
Speaker 1: which says a lot about him. Me. I can't stand
Speaker 1: that song, but maybe it's just because to me, there's
Speaker 1: a point where it just sounds like someone is just
Speaker 1: singing about what they're doing, and I do that every day.
Speaker 1: No one gave me a record deal, alright. So getting
Speaker 1: back to MP three, they had finalized the FOUL format
Speaker 1: and created the standard, but it was just one of
Speaker 1: several possibilities for encoding audio, and it didn't immediately take off.
Speaker 1: It wasn't immediately adopted by consumers. The team had identified
Speaker 1: the Internet as a possible distribute distribution method for MP
Speaker 1: three files, rather than just over telephone lines. They said, well,
Speaker 1: can technically we could send and P three's across the Internet,
Speaker 1: so you could send manageable sized files across this network.
Speaker 1: On July fourteenth, they created the file extension dot MP three.
Speaker 1: Now it would take a little bit longer for software
Speaker 1: to take advantage of this. One of the early programs
Speaker 1: was winamp, which made MP three decoding accessible and from
Speaker 1: that point the file format began to take off. To
Speaker 1: follow would be dedicated MP three players and sites that
Speaker 1: allowed people to upload and download compressed audio files, which
Speaker 1: also indicated a rise in piracy. And then in response
Speaker 1: to the rise in piracy, we saw an increase in
Speaker 1: d r M strategies digital rights management or copy protection
Speaker 1: if you prefer, and that all really in it up
Speaker 1: shaping a lot of the policies and strategies that affect
Speaker 1: the Internet today, So you could say that the MP
Speaker 1: three is one of the reasons why the Internet is
Speaker 1: the way it is right now, and why arguments both
Speaker 1: for and against net neutrality have formulated in certain ways.
Speaker 1: A lot of it is shaped by the MP three.
Speaker 1: So that kind of wraps up this discussion about digital
Speaker 1: audio in general and a little bit on MP three files.
Speaker 1: In the next episode of this series, I will dive
Speaker 1: into a more technical explanation of what is actually going
Speaker 1: on with the MP three compression algorithms. And I bet
Speaker 1: you can't wait to learn all about fast Furrier transforms.
Speaker 1: I know I can't, And like I said, I'll have
Speaker 1: other episodes to sprinkle in between this one and the
Speaker 1: next one and then the third one, so that way
Speaker 1: you won't just get digital audio overload. And if you
Speaker 1: guys have any comments or questions or suggestions for show
Speaker 1: to topics or people I should interview, or maybe people
Speaker 1: I should have on as a guest host, shoot him
Speaker 1: my way. My email is tech Stuff at how stuff
Speaker 1: works dot com, or you can always drop me a
Speaker 1: line on Facebook or Twitter with the handle tech stuff
Speaker 1: hs W and I'll talk to you guys again really
Speaker 1: soon for more on this and thousands of other topics.
Speaker 1: Is it how stuff Works? Dot com