Many Audio/acoustics engineers and researchers and audio hobbyists work with DSP (Digital Signal Processing). Some now and then, some on daily basis. Working on DSP for audio and speech, common challenges to create digital filters are: Noise cancellation, due to interference and Audio and Speech enhancement. And for whom DSP is not his daily job: filter design in general. In this blog, you’ll find out how the ASN Filter Designer may help for both experienced audio engineers and engineers where DSP is not their daily job to create digital filters for audio and speech.

For whom? For those with some and experienced DSP knowledge alike

If you are a audio/acoustics engineer or researcher or hobbyist: ASN Filter Designer is tailored for whom DSP is not his daily job and with some knowledge DSP. For those who need filter design and have to create some signal analysis. But also for those whom DSP is his daily job and want to save time and money. Most engineers who are working with DSP on a daily basis, are usually working with extensive but also expensive tools. Or want to do the maths themselves. Also for them ASN Filter Designer is useful:

  • Intuitive and easy to use
  • Save days of time spending calculating on your own for the price of 2-3 hours of work
  • Few lesser costs then extensive tooling with features you don’t use anyway
  • Automatic code generation: export for further analysis to MATLAB, etc, or to Cortex-M Arm based processors via the Arm CMSIS-DSP software framework

How DSP for Speech and audio benefit from ASN Filter Designer:

  • Experiment with a variety of equalisation, noise cancellation and sound effect audio filtering algorithms
  • Perform data analysis in the frequency domain and via specialised methods, including Cepstral analysis on the streaming data
  • Import your own wav audio files (mono or stereo up to 48kHz) for streaming, and modify the filter characteristics in real-time while listening to the filtered audio stream

Some features for creating digital filters for Audio and Speech:

The sampling frequency may be specified up to 4 decimal places

Sampling frequency

which is useful for designing filters based on fractional sampling frequencies, such as multiples of the 44.1kHz audio standard. Common examples include audio interpolation filters: 44.1kHz × 128 = 5.6448MHz and 44.1kHz × 256 = 11.2896MHz.

Filter orders of up to 499

may be constructed, where this is limited to 200 for streaming audio applications. As with the IIR filters, a FIR’s zeros may be modified by the P-Z editor (Method dropdown list changes to User defined), including the ability of adding poles and converting it into an IIR filter

Audio and user data playback streaming

Signal Generator Controller: 
Choose what you want to listen to; Adjust the amplitude of the input signal
Signal Generator Controller:
Choose what you want to listen to; Adjust the amplitude of the input signal

The signal analyzer allows designers to test their design on audio, real (user) data or synthetic data via the built-in signal generator. Default data playback is implemented as streaming data, providing a simple way of assessing the filter’s dynamic performance, which is especially useful for fixed point implementations. Both frequency domain and time domain charts are fully supported, allowing for design verification via transfer function estimation using the cross and power spectral density functions. As with all other charts, the signal analyzer chart fully supports advanced zooming and panning, as well as comprehensive chart data file export options.

Load .wav for playback

The signal generator allows you to load .wav audio files for playback via the Audio File method. Both mono and stereo formats are fully supported for 8.000, 11.025, 16.000, 22.05 and 44.1kHz. sampling rates. There is no restriction as to the length of the .wav file

You may add extra signals to input audio stream

20 extra signals for an IIR filter this is set at 20, 200 for an FIR

Intuitive data analysis with the mouse

Move the mouse over the chart will automatically produce data markers and data analytics (shown at the bottom right side of the GUI). The signal analyzer is directly coupled to the filter designer GUI. This means that you may modify the filter characteristics. And see the effects in real-time in the signal analyzer. This functionality is very useful when designing audio filters, as the new filter settings can be heard immediately on the streaming audio feed

Digital filters commonly used in audio and speech

speech and audio engineer researcher working on DSP digital filters microphone headphone

The ASN Filter designer includes digital filters commonly used in audio such as:

Read review here:

Top marks from Jacob Beningo

Joseph Yiu ARM Cortex ASN Filter Designer DSP portrait

New book on Arm’s latest processors:  The Definitive Guide to Arm Cortex-M23 and Cortex-M33 Processors. The book is written by Joseph Yiu, Arm’s resident architecture guru. It features benchmarks and experiments with our DSP filter design tooling (ASN Filter Designer) using CMSIS-DSP for Arm’s latest processors

We’re proud that Dr. Sanjeev Sarpal, Director of AI at Advanced Solutions Nederland has provided support in the digital filter design topic. We’re also very pleased to announce that Joseph Yiu’s new book features a chapter on the ASN Filter Designer for AI/IoT applications using the M23 and M33 Cortex-M cores. Advanced Solutions Nederland works closely with Arm’s DSP/architecture team for AI/DSP solutions using their cores. We’re currently working with Arm on releasing whitepapers on the Cortex-M55.

Armv8-M architecture and its features

The Definitive Guide to Arm® Cortex®-M23 and Cortex-M33 Processors focuses on the Armv8-M architecture and the features that are available in the Cortex-M23 and Cortex- M33 processors.

This book covers a range of topics, including:

  • the instruction set
  • the programmer’s model
  • interrupt handling
  • OS support
  • debug features

It demonstrates how to create software for the Cortex-M23 and Cortex-M33 processors by way of a range of examples. This enables embedded software developers to understand the Armv8-M architecture.

Worked out examples with ASN Filter Designer

Joseph Yiu’s new book features a chapter on the ASN Filter Designer for AI/IoT applications using the M23 and M33 Cortex-M cores. Our Director of AI, Dr. Sanjeev Sarpal, has provided support.

“The ASN Filter Designer Professional software supports a wide range of filter types. Its design allows filters to be designed via an interactive user interface, where various parameters can be adjusted and the design’s output can immediately be viewed. It also supports the simulation of the filter’s response so that the simulation outputs can be examined to determine whether the filter meets the requirements of the application. An added bonus, for developers creating software for Cortex-M processors, is that it generates C code that directly call CMSIS-DSP library functions (the designed filters can also be exported to C/C++, Python, Matlab, etc.).”

Joseph Yiu ASN Filter Designer Defining the frequency response of the filter
Defining the frequency response of the filter

“A number of commercial filter-design software tools are designed specifically for filter-design tasks and make it easier tot analyze a filters’ characteristics. For software developers who are not familiar with filter designs, these tools can be a great help” (p. 820). Thereby, Joseph Yiu uses the ASN Filter Designer for worked out examples. He creates a low pass biquad filter for a system with 48kHz sampling rate and with single-precision floating-point data type.

Definitive Guide Arm Cortex Joseph Yiu ASN Filter Designer

Order your copy here

Chebyshev I and Chebyshev II filters: what are the advantages and disadvantages? And what is the syntax of Chebyshev, explained with ASN Filterscript

What are Finite Impulse Respsonse (FIR) Filters? And how to design FIR Filters in ASN Filter Designer and which filters does ASN Filter Designer support?

Butterworth filters have a magnitude response that is maximally flat  in the passband and monotonic overall. Good choice for eg DC and loadcells

The P-Z (pole-zero) editor, comprehensive and easy to use pole-zero editor. Together with useful options not commonly found in other filter design software.

Biomedical devices are one of the golden nuggets of IoT.

What are the challenges?

  •  Tightening of health system budgets
  •  Higher treatment costs due to an aging population
  •  Long patient waiting times
  •  Protection of patient medical data from hackers

Biomedical devices are one of the golden nuggets of IoT. The medical industry has the challenge that health system budgets are being tightened. This is further complicated by an aging population with higher life expectancy and higher demands for medical treatment. As a consequence, serving a population with an increasing aging population means that there will be longer patient waiting times and increased medical costs.
Smart medical devices are viable solution to facilitate this for many people, especially the elderly who greatly value their independence.

Exercises at home

A lot of time is lost travelling to therapy appointments, and for elderly people with limited mobility, this is not always possible. A much more efficient method is to allow patients to do their exercises at home. Smart sensors provide a simple way of ‘measuring if they do their exercises correctly’ and if they are on track for recovery. Patients don’t have to travel and spend hours sitting in a waiting room. The therapist just has to follow the patients’ developments and make an appointment when necessary. And at an appointment, the therapist can easily dive into details, because the patient has followed his recovery themselves. This frees up the therapists’ time, and allows them to focus on the patients with more serious injuries.


Meanwhile, there is the need for protection of patient medical data from hackers. Hospitals are an interesting target for terrorists and other evil-doers. That’s why prevention from being hacked is very important. And if you are being hacked, then you want to know as soon as possible, so you can take action in time, before a hacker has caused any serious damage.

In the IoT of medical devices, algorithms play an important role. Use our algorithms to filter and analyse your ECG and EMG signals. Read more about help with your challenges:

Advanced Solutions Nederland is happy to announce that the ASNFD filtering Arm MDK5 software pack now avalailable for download! The filtering pack provides MDK users with an easy way of ASN’s IP.

Keil MDK is the most comprehensive software development solution for Arm-based microcontrollers. For MDK, additional software components and support for microcontroller devices is provided by software packs. Download here

UI experience 2020 pack

After downloading the ASN Filter Designer, most people just want to play with the tool, in order to get a feeling of whether it works for them. But how do you get started with the ASN Filter Designer? Based on some great user feedback, ASNFD v4.4 now comes with the UI experience 2020 pack. This pack includes detailed coaching tips, an enhanced user experience and step-by-step instructions to get you started with your design.

A quick overview of the ASN Filter Designer v4.4 is given below, and we’re sure that you’ll agree that it’s an awesome tool for DSP IIR/FIR digital filter design!

The ASN Filter Designer has a fast, intuitive user interface. Interactively design, validate and deploy your digital filter within minutes rather than hours. However, getting started with DSP Filter Design can be difficult, especially when you don’t have deep knowledge of digital signal processing. Most people just want to experiment with a tool to get a feeling whether it works for them (sure, there are tutorials and videos). But where do you start?

Start experimenting with filter design immediately

That’s why we have developed the UI Experience 2020 pack. Based on user feedback, we’ve created detailed tooltips and animations of key functionality. Within minutes, you’ll get a kick-start into functionalities such as chart zooming, panning and design markers.

Coaching tips, enhanced user experience, step-by-step instructions

Based on user feedback, the UI Experience 2020 pack includes:

  • Extensive coaching tips
  • Detailed explanations of design methods and types of filters
  • Enhanced user experience:
    • cursors
    • animations
    • visual effects
  • Short cuts to detailed worked solutions, tutorials and step-by-step instructions

Feedback from the user community has been very positive indeed! By providing detailed tooltips and animations of key functionality, the initial hurdle of designing a filter with your desired specifications has now been significantly simplified.

So start with the ASN Filter Designer right away, and cut your development costs by up to 75%!

ASN Filter Designer box
ASN Filter Designer box, the powerful DSP Filter Designer platform