Hello DIY Audio Community,
We are a team of engineering students and audio enthusiasts working on a new approach to speaker design that leverages AI-driven parametric modeling and large-scale 3D printing to create customizable, highly optimized sound systems. Our goal is to explore whether these technologies can enhance acoustic performance, reduce material waste, and provide new levels of customization in speaker design.We would love to hear your thoughts, experiences, and concerns on this topic, and we have a few questions to guide the discussion:
1. Current Challenges in Speaker Design & Performance
- What are the biggest challenges you face when designing or modifying speaker enclosures?
- Have you ever encountered limitations in traditional speaker materials (wood, aluminum, composites)?
- How do you currently approach tuning and optimizing speakers for different acoustic environments?
2. AI-Driven Acoustic Optimization
- Do you think AI and parametric design could offer improvements in acoustic tuning and speaker design efficiency?
- Would you consider using a software tool that automatically generates optimized speaker designs based on acoustic parameters?
- What level of customization and control would you expect from such a system?
3. 3D Printing & Manufacturing Feasibility
- Have you experimented with 3D printing for speaker enclosures or acoustic components?
- What are the biggest challenges you see in using 3D printing for high-performance speaker construction?
- Do you think non-rectangular or organic speaker shapes (enabled by 3D printing) could improve sound dispersion and resonance control?
4. Adoption & Market Interest
- If a modular, AI-optimized, 3D-printed speaker system was available, what would convince you to try it?
- Would lighter, more transportable designs make a significant impact for professional applications (event sound systems, rentals, etc.)?
- Are there specific features you would want in an AI-generated speaker system (e.g., real-time acoustic adaptation, modular assembly, material choices)?
5. Open Discussion & Feedback
We highly appreciate any thoughts, feedback, or additional perspectives that could help us refine our approach. If you have experience with AI in acoustics, 3D printing in speaker design, or have faced real-world sound engineering challenges, we’d love to hear from you!Looking forward to an insightful discussion.
Thanks in advance
I would like to know how to put speakers in the room. Obviously, I'd like to know which kind of room would accomodate my speakers. I'd like to know...
One of the standard approaches is to use a flat target for anechoic on-axis response, and then a power response that decreases slightly with increasing frequency. In most typical home listening rooms, this gives a detailed but pleasant sound. The CTA-2034 / SPINORAMA test typically addresses this.
For an inexperienced designer, yes, assuming enough design targets are included. If the tool can get near what an experienced human designer can do, it should be useful.
Yes, as a starting point at least. If you could simply input drivers and generate a good starting design that takes driver limitations into account, it might speed things up or highlight problem areas in the approach.
The ability to analyze on-axis and off-axis behavior, specify cross points and slopes, baffle layout (X,Y,Z), some kind of deviation from target response control so crossovers could be simplified or made as complex as desired to get near the target response.
Analysis of displacement and power limits so crossover points and their affect on SPL could be shown. Impedance/phase, step response, group delay, power dissipation for resistors.
Print time/cost
Good subjective review and measurement set by a 3rd party.
This seems like an interesting angle, if you can come up with a lightweight enclosure that is more durable and inert than typical pro-sound approaches. Some lightweight plastic enclosures on the market seem to have a reputation for being cheap, resonant, and fragile. That perception could be a bit of a challenge to overcome as well.
As an engineer for nearly 50 odd years that has been exposed to "AI" nonsense on and off for pretty much all of it I am tempted to sound-off at length but shall refrain. If you want to reach engineers I would suggest dropping the marketing term and replacing it with what you intend to use.
Shape optimisation is well developed and is generally more efficient using techniquese other than neural networks (assumng that is what you intend to use) because there aren't that many parameters. An example but there are plenty of others.
Although additive manufacture is popular with DIYers it is expensive and not well suited to commercial speaker activity. Node Audio is perhaps a good example. The speaker was designed using low cost consumers drive units presumably (guessing on my part) with a view to selling into the Bose/B&O market sector. It's a well engineered speaker that uses additive manufacture well but the cost of manufacture is so high the only viable market sector is the miniscule ultra-fi at £34-38k a pair.
PA speakers are already acoustically shaped, mass produced in plastic and cost peanuts. The high performance midfield studio monitors are also already acoustically shaped, sold at competitive prices not much above a DIY prices and offer a technical performance DIY would struggle to match.