W3C home > Mailing lists > Public > public-audio@w3.org > April to June 2012

iZotope's Web Audio Considerations

From: Alistair MacDonald <al@signedon.com>
Date: Wed, 20 Jun 2012 10:09:11 -0400
Message-ID: <CAJX8r2nL4PmxbfuZZa0=+XGKh_eRNUMdMf-H2TJowiefenj9vw@mail.gmail.com>
To: public-audio@w3.org
Cc: Craig Hanson <chanson@izotope.com>
A couple of months ago I sat down with Izotope, an audio company in Boston
specializing in DSP for games and music/audio production. They licence code
to EA, Harmonix, Microsoft (XBox) etc.

Izotope had some great feedback; as well as some questions and suggestions
which may be worth adding to the bug tracker where they have not been
covered already.

I wanted to introduce Lead Software Engineer Craig Handson to the mail list
discussions, as I think his input will be valuable to the group.

Craig, thanks again for taking the time to review in detail the work so far.

I have attached the PDF from Craig to this email, but I am also posting the
content of the PDF here so that e have it in the mail list records.


iZotope Web Audio Considerations
*I. Overview

*The current web audio specification is suitable for implementing small,
lightweight signal processing algorithms. The use case of this API is a
very important consideration when it comes to its architecture. If the
intent is to provide a simple interface for implementing inexpensive,
lightweight signal processing routines, it would seem the existing
architecture is sufficient. If the intent is to build a robust environment
that can handle the adoption of more intensive DSP, we are of the opinion
that the underlying technology will impose limitations that render the
implementation of intensive real-time DSP impossible. The two main focal
points to bear in mind when constructing a robust real-time DSP
architecture are:

*1. Non-pre-emptible processing – The DSP must be allowed to process

without interruption or dropouts will occur. 2. Worst case analysis –
Average CPU consumption metrics are not important in a
real-time signal processing system. Only the worst case metrics should be
used to evaluate whether or not a DSP system can reliably run.*
We will elaborate further on these two topics in section III of this
document. Prior to this, in section II, we discuss some general
modifications and things to keep in mind for the API itself. Section IV
presents an example architecture that we believe would allow for a robust
real-time DSP environment. Section V presents matters of intellectual
property protection that will allow for high quality DSP to be developed
for this platform.

*II. API Considerations

*As far as the API itself is concerned, the majority of the implementation
seems sound. The AudioNode and AudioParam interfaces generally make a lot
of sense. There are, however, a few additions and considerations for the
API we’d like to point out.

*1. Addition of a query and notification system on latency changes. This
provide the DSP developer and the environment with a way to remain in sync
as the parameters of a DSP algorithm change. As there are several different
forms of latency, we shall clarify the type of latency we are discussing
here is latency from input to output in a given DSP algorithm. The amount
of latency is the number of invalid initial samples that should be removed
from the beginning of the DSP output.*
As an example: a given DSP algorithm may report a latency of 1024 samples.
If the audio system’s buffer size is 512 samples, the first 2 buffers (1024
samples) to come out of the DSP algorithm in the first buffer should be
thrown away. The first valid output sample will be the first sample of the
3rd buffer. Additionally, the end of the audio stream should be extended to
obtain an additional
samples from the DSP. In this example, it can be done by streaming an extra
2 buffers of zeros as input to the DSP. The DSP will output the final 1024
valid samples in those 2 buffers. This behavior is considered the ‘system
delay’ or ‘latency’ of a DSP algorithm.

*Latency reporting is perhaps best done by way of high precision floating
point seconds. Something similar to implementation used in Mac OS X Audio
Units is best. For more details, see ‘kAudioUnitProperty_Latency’ in:

*2. CPU Monitoring should be done on a ‘worst case scenario’ basis. The cpu
load of signal processing algorithms is not usually constant. Ideally, DSP
should be developed with an eye on keeping the CPU load even across
buffers. In practice, this can be difficult for some algorithms and there
may be CPU spikes during processing. Poorly designed signal processing
algorithms may have extremely large CPU spikes that prevent real-time
processing. To ensure that CPU load will never go above 100% and the audio
system will remain glitch-free, CPU levels should be measured on a
worst-case basis. To illustrate this, let’s take an example algorithm that
requires some audio analysis to take place at some fixed time interval (say
every 8192 samples). Let’s assume the audio buffer size is 1024 samples and
we are trying to process in realtime. Extra processing is going to take
place inside the algorithm every 8 buffers and depending on the intensity
of this processing, it may well be over 100% while processing every 8th
buffer. As a consequence, you will see a CPU spike every 8 buffers and an
audio dropout every 8 buffers. If the analysis portion of this algorithm is
very heavy on CPU load and the other processing portion is very light, you
could see an average CPU load that looks as if it should work in real-time.
But don’t be fooled, worst-case CPU is what matters for real-time DSP.

*3. Many DSP algorithms have boolean and integer parameters in
addition to floating
point parameters. As we can only see floating point representations of
parameters in the current API draft. This can work perfectly fine, but you
may want to think about how to standardize this further. Many DSP
algorithms also use boolean and integer parameters. Perhaps a solution
similar to the VST interface would be satisfactory. There, Steinberg forces
parameters to have a range between 0.0f and 1.0f (inclusive) and other
types are handled by typecast. You can find more details on the VST
interface itself here: http://www.gersic.com/vstsdk/.

*III. The DSP Environment

*True real-time DSP implemented in a web browser could change the way
musicians, gamers and media producers work in the future. In order to make
the API scalable and future-proof, a highly performant environment is
necessary. We feel that Javascript itself cannot provide such an
environment. There are a few key issues we
*have noted in our discussions on the topic and the common thread running
through all these issues is the assurance that sufficient processing is
available at all times. Predictable CPU availability is absolutely critical
to the effectiveness of real-time digital signal processing. As stated in
the overview, non-pre-emptible processing and worst case analysis are the
main issues to overcome. To that end, there are some key considerations:

*1. A dedicated DSP processing thread is required to ensure the audio has
highest priority possible during processing. The thread should never be
interrupted due to non-DSP code.

*2. The general overhead of Javascript will limit the scalability and
ability of
developers to implement intensive, high performance DSP.

*3. Garbage collected languages are not conducive to real-time audio
applications as there is no guarantee of when the collector will run. This
makes it impossible to predict what the actual CPU of the system will be
and to determine whether or not a signal processing routine will be able to
operate in real-time.

*There are many effects that have mass market appeal which we believe would
not be possible under the current architecture. The T-Pain Effect is a
specific example of one such effect.
The general consensus is that audio going through a Javascript layer will
likely end up with problems similar to the Android audio system. As the
realization for the need for more performance becomes a problem, a push to
huge audio buffers will be inevitable. That reliance on large audio buffers
will make latency a real problem for anyone that needs a low-latency
(5-10ms) solution. Low latency audio has been impossible for developers to
achieve on Android without bypassing the audio architecture completely.
There is also no way to take advantage of machine optimized functions.
There are large speed ups in processing that could be achieved if optimized
math functions could be used. The most viable solution for this is an
LLVM-based just in time solution for the browser. Something similar to the
behavior in Google’s Native Client SDK:

*IV. An LLVM-based proposal

*An LLVM-based implementation would compile, link and run on-the-fly in the
browser. This would allow developers to create independent byte-code that
would be deployed to a user’s machine through the browser and would run in
a sandboxed area. Here is the process and how this approach is
advantageous: 1. Developers write DSP code in C, C++, or related languages
that are not garbage collected. Which has two distinct advantages:

* a. Far less overhead than Javascript. There is no doubt the code will run

much faster.

b. No garbage collection. This means writing real-time code is a

*2. LLVM would turn the C/C++ code written by the developer into bytecode
(intermediate form). This is intermediate form is distributed by the
developer for use in the application. 3. When deployed, LLVM compiles
intermediate form code into optimized intermediate form for the target
platform. This can take advantage of optimizations made by the LLVM
compiler and will produce code that runs significantly faster than what
could run with the Javascript layer.

*V. Intellectual Property Protection*
For browser-based audio solutions, there should be some concern over
intellectual property. As this code tends to be downloaded directly to a
user’s computer through the web browser, how will companies ensure
protection over their IP? If there is no good defense for intellectual
property, it will really limit the potential of high quality DSP to be
produced for the platform. We should ensure that closed-source audio
effects can be made available with no concerns over intellectual property.*

I put together some links below for anyone who is interested in learning
more about iZotope's offerings in the music/gaming industries.

Visual waveform editing with RX 2

3D frequency analysis

iZotopes game audio solutions

Alistair MacDonald
SignedOn, Inc - W3C Audio WG
Boston, MA, (707) 701-3730
al@signedon.com - http://signedon.com

Received on Wednesday, 20 June 2012 14:09:50 UTC

This archive was generated by hypermail 2.4.0 : Friday, 17 January 2020 19:03:05 UTC