Thursday, May 26, 2016

Writing a reverb filter from first principles

WARNING/DISCLAIMER: Audio programming always carries the risk of damaging your speakers and/or your ears if you make a mistake. Therefore, remember to always turn down the volume completely before and after testing your program. And whatever you do, don't use headphones or earphones. I take no responsibility for damage that may occur as a result of this blog post!

Have you ever wondered how a reverb filter works? I have... and here's what I came up with.

Reverb is the sound effect you commonly get when you make sound inside a room or building, as opposed to when you are outdoors. The stairwell in my old apartment building had an excellent reverb. Most live musicians hate reverb because it muddles the sound they're trying to create and can even throw them off while playing. On the other hand, reverb is very often used (and overused) in the studio vocals because it also has the effect of smoothing out rough edges and imperfections in a recording.

We typically distinguish reverb from echo in that an echo is a single delayed "replay" of the original sound you made. The delay is also typically rather large (think yelling into a distant hill- or mountainside and hearing your HEY! come back a second or more later). In more detail, the two things that distinguish reverb from an echo are:

  1. The reverb inside a room or a hall has a much shorter delay than an echo. The speed of sound is roughly 340 meters/second, so if you're in the middle of a room that is 20 meters by 20 meters, the sound will come back to you (from one wall) after (20 / 2) / 340 = ~0.029 seconds, which is such a short duration of time that we can hardly notice it (by comparison, a 30 FPS video would display each frame for ~0.033 seconds).
  2. After bouncing off one wall, the sound reflects back and reflects off the other wall. It also reflects off the perpendicular walls and any and all objects that are in the room. Even more, the sound has to travel slightly longer to reach the corners of the room (~14 meters instead of 10). All these echoes themselves go on to combine and echo off all the other surfaces in the room until all the energy of the original sound has dissipated.

Intuitively, it should be possible to use multiple echoes at different delays to simulate reverb.

We can implement a single echo using a very simple ring buffer:

    class FeedbackBuffer {
        unsigned int nr_samples;
        int16_t *samples;

        unsigned int pos;

        FeedbackBuffer(unsigned int nr_samples):
            samples(new int16_t[nr_samples]),

            delete[] samples;

        int16_t get() const
            return samples[pos];

        void add(int16_t sample)
            samples[pos] = sample;

            /* If we reach the end of the buffer, wrap around */
            if (++pos == nr_samples)
                pos = 0;

The constructor takes one argument: the number of samples in the buffer, which is exactly how much time we will delay the signal by; when we write a sample to the buffer using the add() function, it will come back after a delay of exactly nr_samples using the get() function. Easy, right?

Since this is an audio filter, we need to be able to read an input signal and write an output signal. For simplicity, I'm going to use stdin and stdout for this -- we will read 8 KiB at a time using read(), process that, and then use write() to output the result. It will look something like this:

    #include <cstdio>
    #include <cstdint>
    #include <cstdlib>
    #include <cstring>
    #include <unistd.h>

    int main(int argc, char *argv[])
        while (true) {
            int16_t buf[8192];
            ssize_t in = read(STDIN_FILENO, buf, sizeof(buf));
            if (in == -1) {
                /* Error */
                return 1;
            if (in == 0) {
                /* EOF */

            for (unsigned int j = 0; j < in / sizeof(*buf); ++j) {
                /* TODO: Apply filter to each sample here */

            write(STDOUT_FILENO, buf, in);

        return 0;

On Linux you can use e.g. 'arecord' to get samples from the microphone and 'aplay' to play samples on the speakers, and you can do the whole thing on the command line:

    $ arecord -t raw -c 1 -f s16 -r 44100 |\
        ./reverb | aplay -t raw -c 1 -f s16 -r 44100

(-c means 1 channel; -f s16 means "signed 16-bit" which corresponds to the int16_t type we've used for our buffers; -r 44100 means a sample rate of 44100 samples per second; and ./reverb is the name of our executable.)

So how do we use class FeedbackBuffer to generate the reverb effect?

Remember how I said that reverb is essentially many echoes? Let's add a few of them at the top of main():

    FeedbackBuffer fb0(1229);
    FeedbackBuffer fb1(1559);
    FeedbackBuffer fb2(1907);
    FeedbackBuffer fb3(4057);
    FeedbackBuffer fb4(8117);
    FeedbackBuffer fb5(8311);
    FeedbackBuffer fb6(9931);

The buffer sizes that I've chosen here are somewhat arbitrary (I played with a bunch of different combinations and this sounded okay to me). But I used this as a rough guideline: simulating the 20m-by-20m room at a sample rate of 44100 samples per second means we would need delays roughly on the order of 44100 / (20 / 340) = 2594 samples.

Another thing to keep in mind is that we generally do not want our feedback buffers to be multiples of each other. The reason for this is that it creates a consonance between them and will cause certain frequencies to be amplified much more than others. As an example, if you count from 1 to 500 (and continue again from 1), and you have a friend who counts from 1 to 1000 (and continues again from 1), then you would start out 1-1, 2-2, 3-3, etc. up to 500-500, then you would go 1-501, 2-502, 3-504, etc. up to 500-1000. But then, as you both wrap around, you start at 1-1 again. And your friend will always be on 1 when you are on 1. This has everything to do with periodicity and -- in fact -- prime numbers! If you want to maximise the combined period of two counters, you have to make sure that they are relatively coprime, i.e. that they don't share any common factors. The easiest way to achieve this is to only pick prime numbers to start with, so that's what I did for my feedback buffers above.

Having created the feedback buffers (which each represent one echo of the original sound), it's time to put them to use. The effect I want to create is not simply overlaying echoes at fixed intervals, but to have the echos bounce off each other and feed back into each other. The way we do this is by first combining them into the output signal... (since we have 8 signals to combine including the original one, I give each one a 1/8 weight)

    float x = .125 * buf[j];
    x += .125 * fb0.get();
    x += .125 * fb1.get();
    x += .125 * fb2.get();
    x += .125 * fb3.get();
    x += .125 * fb4.get();
    x += .125 * fb5.get();
    x += .125 * fb6.get();
    int16_t out = x;

...then feeding the result back into each of them:


And finally we also write the result back into the buffer. I found that the original signal loses some of its power, so I use a factor 4 gain to bring it roughly back to its original strength; this number is an arbitrary choice by me, I don't have any specific calculations to support it:

    buf[j] = 4 * out;

That's it! 88 lines of code is enough to write a very basic reverb filter from first principles. Be careful when you run it, though, even the smallest mistake could cause very loud and unpleasant sounds to be played.

If you play with different buffer sizes or a different number of feedback buffers, let me know if you discover anything interesting :-)

Wednesday, July 11, 2012

Comparing objects in C++

The standard C++ pattern for comparing and ordering objects is to overload operator<() for your class. This function is what all the standard containers (std::set, std::priority_queue, etc.) and algorithms (std::sort, std::binary_search, etc.) use for comparing objects.

So if you have a class that you would like to put in a standard container, you have to overload operator<(). Your class usually has more than one member, and you usually want to order your objects first by the value of one member, then by the value of another member, and so on. For example, if you have a class person with string members firstname and lastname, and you would like a "phone book" ordering, you would order by lastname first, then by firstname, e.g.:

Anderson, Clive
Anderson, Lucy
Anderson, Thomas
Armstrong, Lance
Armstrong, Neil

To achieve this using operator<(), implemented only in terms of std::string::operator<(), you could do something like this:

struct person
    std::string firstname;
    std::string lastname;

    bool operator<(const person &other) const
        /* Order first by lastname */
        if (lastname < other.lastname)
            return true;
        if (other.lastname < lastname)
            return false;

        /* The lastnames were equal, so try to order by firstname instead */
        return firstname < other.firstname;

This code is not optimal. To see why, consider a case where you have two persons with the same lastname. The first check will fall through (lastname < other.lastname is false); so will the second (other.lastname < lastname is also false). Each check had to loop over the lastname when a single loop should have sufficed.

Fortunately, std::string happens to implement a member function compare() which returns an int. The semantics are similar to C's strcmp(a, b), which also returns an int. The return value is less than 0 if a < b, 0 if they are equal, or greater than 0 if a > b. Using this function, we can implement a much more efficient operator<():

struct person
    std::string firstname;
    std::string lastname;

    bool operator<(const person &other) const
        int d =;
        if (d < 0)
            return true;
        if (d > 0)
            return false;

        /* The lastnames were equal, so try to order by firstname instead */
        return firstname < other.firstname;

To see the difference in running time, we can implement a simple loop which inserts the same element many times to a multiset:

int main(int argc, char *argv[])
    std::multiset<person> persons;

    for (unsigned int i = 0; i < 1000000; ++i)
        persons.insert(person("Thomas", "Anderson with a rather long last name for the sake of the argument"));

We exaggerate the number of elements and the length of the lastname in order to amplify the difference. Running this on my laptop, it takes approximately 3.9 seconds to run the original code and 2.9 seconds to run the new version.

This is all well and good, but the actual problem runs a bit deeper than this. What if our code uses other compound data types than strings? Take e.g. std::pair. It is hopelessly broken, precisely because it doesn't implement a compare() function! std::pair only implements operator<() and only expects its elements to implement operator<() too. Have a look at the libstdc++ implementation (simplified):

template<class _T1, class _T2>
inline bool operator<(const pair<_T1, _T2>& __x, const pair<_T1, _T2>& __y)
    return __x.first < __y.first
        || (!(__y.first < __x.first) && __x.second < __y.second);

Can you spot the performance bug? Yep, it calls checks both __x.first < __y.first and __y.first < __x.first in the worst case. This also means that std::pair<std::string, std::string> has exactly the same problem as our first implementation of struct person.

In order to show just how bad this really is, consider the case where we have nested pairs:

typedef std::pair<int, int> p1; // 2 elements
typedef std::pair<p1, p1> p2;   // 4 elements
typedef std::pair<p2, p2> p3;   // 8 elements
// ...
typedef std::pair<p5, p5> p6;   // 64 elements

This is not a realistic example per se, but it illustrates very well how big the problem really is. Let's assume we have an object x6 constructed in the following way:

p1 x1(0, 0);
p2 x2(x1, x1);
// ...
p6 x6(x5, x5);

What happens when you try to compare x6 to itself like this?

if (x6 < x6)
    /* ... */;

Let's take a step back. x6 has 64 int elements, which can be reached in the following ways:


Intuitively, we should only need to perform 128 comparisons in the worst case (two comparisons for each pair of corresponding elements from the two objects). If we had two arrays of 64 ints, we would do it like this:

int compare(const int a[64], const int b[64])
    for (unsigned int i = 0; i < 64; ++i) {
        if (a[i] < b[i])
            return -1;
        if (b[i] < a[i])
            return 1;

    return 0;

In order to answer the question posed ("How many comparisons between two ints are we actually making when we compare x6 against itself?"), we can simply program it using a wrapper class for int that counts the number of comparisons:

static unsigned int nr_comparisons = 0;

struct myint
    int value;


    myint(int v):

    bool operator<(const myint &other) const
        return value < other.value;

Now we just have to change the definition of p1 from

typedef std::pair<int, int> p1;


typedef std::pair<myint, myint> p1;

and finally print nr_comparisons. The answer? 729.

Because std::pair has three comparisons in the worst case, instead of just two (which would have been sufficient), the complexity of comparing nested pairs has just climbed from 2^n (where n is the number of levels of pairs) to 3^n. That's pretty bad!

Part of the solution, as employed by std::string and our improved struct person, is to define the most fundamental comparison between objects as a function that can tell you whether a < b, a == b, or a > b in a single call rather than determine this using two calls. It is clear that the two are semantically equivalent (you can both define operator<() in terms of compare() and the other way around), but one is computationally superior for compound objects.

This is still not the full story, however. We wouldn't get any performance improvement from std::set if we changed it to call compare() instead of operator<() — because it doesn't need to compare both ways! In fact, if we changed it, we would now find that std::set<int> operations take more time, since calling compare() on an int would have to check both a < b and b < a even when std::set only needs to know the result of one of them! (This is of course tighly coupled to the std::set implementation — implemented as a tree, lookups would typically traverse the tree by comparing the element that is searched for with the current node, and update the current node depending on the result of the comparison.)

The real solution, therefore, seems to be to implement both operator<() and compare() for all types. std::pair's would look something like this:

bool operator<(const pair &other) const
    int d =;
    if (d < 0)
        return true;
    if (d > 0)
        return false;

    return second < other.second;

int compare(const pair &other) const
    int d =;
    if (d != 0)
        return d;


Now containers and algorithms can use the most efficient one — std::set would still use operator<() on its elements, but std::pair::operator<() would now use compare() (for its first element), and so on.

Maybe we could adopt Perl's <=> operator for the next version of C++?

Tuesday, January 26, 2010

Space invaders?

After my exams in December, I relaxed by writing a sort of space game using C++/SDL/OpenGL:

I ripped the sprites from Space Invaders and Galaga/Galaxian, please forgive me. If whoever wants to play/hack, the source code can be found here:

The video is a bit poor, mostly because the frame rate is supposed to be 60 FPS, but the Ogg/Theora capture was 25 FPS while the actual gameplay was probably closer to ~10 while doing the capture. Need to fix that. It looks better when playing.

Thursday, September 10, 2009

First Jato release

So I somewhat promised to say something more on my project for the Google Summer of Code.

I participated for the first time, and it was really a great experience. This is the first time I've been paid to do what I would probably have done in either case (because I immensely enjoy it), namely to work on an interesting free software project. So this time it was Jato, a new implementation of the Java Virtual Machine.

Jato is written in C and aims to be a JIT-only compiler/VM. So before the summer started, it wouldn't run a lot of Java programs. It couldn't even run the trivial "Hello World", but more about that later. It could do a few things like (java.lang.)String operations, but that was mostly because it was riding piggyback on another VM, Jam VM, which would load classes and interpret a lot of the library code (i.e. most of the standard Java API implemented by GNU Classpath).

My own project was to replace the parts that were borrowed from Jam VM with completely new, shiny code. Well, in fact, I had already worked on a standalone library called cafebabe, which would parse the Java .class file and present it to C programs using a very thin layer of structs -- the idea was to do as little as possible with the actual data and just make it easily accessible, e.g. so cafebabe doesn't do any verification of the bytecode or make sure that a class is its own superclass.

So we linked this library with Jato, and that worked pretty well. (I believe strongly in modularisation; with the class loader in a separate library, there's no way to do stupid things like making the class loader itself depend on the rest of the VM for functioning properly.) There were problems, of course, the biggest being that after developing in my own private branch for a couple of weeks, the rest of the project with its three other GSoC student participants was moving ahead too quickly for me to keep up; I had to "fix" just about every new mainline commit, since most of the VM data structures (classes, methods, fields) now had different names, different fields, etc.

At around this point, we started to notice that Jam VM wasn't being used for nearly as little as just class loading. In fact, static initializers (the "<clinit>" methods) and their calls were all being interpreted and executed by Jam VM, not the JIT compiler of Jato. And of course, once we started using Jato for those methods which had previously been executed by Jam VM, we found tons of bugs everywhere: The core VM (mostly my code replacing that of Jam VM), including improperly implemented Java semantics, missing bytecode instruction handlers, and the compiler (instruction selection, liveness analysis, register allocation). But it was fun, and extremely educative.

Did you know that a simple System.out.println() will make a whopping 650550 Java-method calls? That's using GNU Classpath for the Java API.

So we had to implement a lot of stuff just to make that work. In fact, we have so much infrastructure that we can even run a few other programs. And thus it was decided that it was time to make a release. The version 0.0.1 announcement:

The "next big" missing feature is garbage collection. I expect that'll be version 0.0.2. In other words, if you're interested in Java, garbage collection, or just compilers in general, you're welcome to join us...

Our team consisted of:
  • Pekka Enberg; Original creator, project manager and mentor.
  • Tomek Grabiec; His original project proposal included implementing exception handling, but he ended up somwhat like Ingo Molnar of the Linux kernel; Tomek also implemented a generic radix tree, implemented the basic threading support (java.lang.Thread), rewrote large parts of the register allocator, wrote the VM side of the JNI interface from scratch, and also did a lot of other core-VM work. Tons of other things too, including a lot of debugging.
  • Arthur Huillet; Floating-point support, register allocator fixes, other missing bytecodes, also a lot of debugging. Various other things.
  • Eduard-Gabriel Munteanu; Ported Jato mostly to x86-64. A tough task, since the i386 parts were moving at close to light speed.

The Jato IRC logger

Here's the recipe for the Jato IRC logger. Nothing fancy, but works surprisingly well.

settings = {
core = {
real_name = "#jato IRC logger";
user_name = "vegard";
nick = "jato-irc-logger";

"fe-text" = {
actlist_sort = "refnum";

"fe-common/core" = {
autolog = "Yes";
autolog_path = "logs/$0/%Y-%m-%d.txt";

servers = (
address = "";
chatnet = "Freenode";
port = "6667";
autoconnect = "Yes";

chatnets = {
Freenode = {
type = "IRC";
autosendcmd = "/^msg nickserv identify vegard password";

channels = (
name = "#jato";
chatnet = "Freenode";
autojoin = "Yes";

screen irssi --config=irssi-config

#! /bin/bash -e

screen -c screenrc -dmS jato-irc-logger

# m h  dom mon dow   command
0 * * * * rsync -r -t --chmod=a+r jato-irc-logger/logs/#jato/ vegardno@hostname:www_docs/jato-irc-logs

#!/bin/sh -e

cd /home/vegard/jato-irc-logger
sudo -u vegard ./ &

exit 0

Wednesday, June 17, 2009

kmemcheck in mainline

First of all, I should say that on April 22, I went to Denmark to give a talk on kmemcheck. I was invited to DIKU (Datalogisk Institut på Københavns Universitet) by Julia Lawall, who held a workshop on Coccinelle (or, more generally, "finding bugs in operating system software"). It was really nice to be there, not (just) because I got a chance to talk about kmemcheck, but because I learned so much from all the other talks! Feel free to check out my slides.

I had asked my university (the University of Oslo) beforehand to sponsor the trip in exchange for a trip report, but I got no reply to my e-mail. I guess they don't see any value in collaboration with universities abroad.

And now, for the news: Yesterday, kmemcheck was merged in mainline Linux! It is quite an incredible feeling after having spent so much time to make it work properly... (Not to mention the rebase marathon that ensued after Linus initially rejected it)

I had also asked Redpill Linpro (a Norwegian/Swedish open source developer) beforehand to sponsor my work on kmemcheck for the summer, but they apparently weren't interested. At least I got a polite reply. (Instead, I got a stipend from Google for working on Jato for the summer, but more on that in a later post!)

Thursday, May 21, 2009

Hiragana tutor

An evening spent with Unicode charts, HTML, CSS, and JavaScript resulted in this:

The online Hiragana tutor

If you find any errors, please tell me.