Hey everyone, welcome back to My Weird Prompts. I am Corn, and I am here with my brother, as always. We have a really technical one today that I think is going to be right up our alley, especially considering how much time we have spent tinkering with the setup in this house. It is February twentieth, twenty twenty-six, and the world of home automation has moved so fast, but some of these fundamental audio problems just never seem to go away.
Herman Poppleberry here. And yeah, Corn, when I heard the prompt from Daniel today, I immediately thought of the hours we spent trying to get the audio in the kitchen to not sound like it was coming from inside a tin can while the living room sounded like a concert hall. I remember back in twenty twenty-four when we first installed those ceiling speakers and realized that the drywall was basically acting like a giant drum. Today's prompt from Daniel is about the optimal way to handle equalization and digital signal processing in a multi-room audio setup, specifically using tools like Snapcast and Home Assistant. It is a deep dive into the architecture of sound.
It is a classic problem for anyone who moves beyond just buying a bunch of smart speakers and actually wants a high-fidelity, synchronized experience. Daniel is using Snapcast, which for those who do not know, is an incredible open-source project that allows for perfectly synced audio over a network. It is basically a client-server model where the server sends out a stream, and the clients—which could be anything from a Raspberry Pi to an old laptop—play it back in perfect unison. But as Daniel pointed out, once you start adding Home Assistant and Music Assistant into the mix, you have a lot of different places where you can tweak the sound. You have got the source, the server, the stream, the client, and the physical speaker itself.
Exactly. You have the hardware level, which might be the physical knobs on a Behringer speaker like Daniel mentioned, or the built-in digital processing inside a Sonos or an Apple HomePod. Then you have the software level at the client, then the server level in Snapcast, and then the orchestration level in Home Assistant. If you are not careful, you end up with what I like to call the EQ lasagna. You are layering filters on top of filters, and by the time the sound hits your ears, it is a phase-shifted, muddy mess. It is like trying to look through five different pairs of sunglasses and wondering why everything looks dark and blurry.
The EQ lasagna. I like that. It sounds delicious but tastes like static. So, Herman, let us start with the core of Daniel's question. If you are designing this from scratch, what is the philosophy? Do you go for the pure, unadulterated signal from the source and let the speakers handle themselves, or do you try to centralize the brain of the operation? I know we have gone back and forth on this in our own house, especially when we were trying to get the podcast audio to sound consistent while we were moving between the office and the workshop.
It is a great question, and to answer it, we have to look at what we are trying to achieve. In a multi-room setup, the goal is usually consistency. You want to walk from the bedroom to the hallway to the kitchen and feel like the audio is a continuous blanket of sound. The problem is that every room has a different acoustic signature. Your kitchen, with its hard tiles and stainless steel, is going to reflect high frequencies like crazy. Your living room with a big rug and a sofa is going to soak them up. If you use a speaker like the Behringer Truth series that Daniel mentioned, those are studio monitors. They are designed to be flat, but they have these little switches on the back for room compensation. If you flip those switches AND use a software EQ, you are asking for trouble.
Right, so if you send the exact same signal to every room, they are going to sound completely different anyway because of the physics of the space. So, if we follow Daniel's thought of trying to do things the technically correct way, we have to account for those room dynamics. But Daniel is worried about that weird sounding output when you layer EQs. Why does that happen exactly? Why can we not just add five decibels of bass at the server and then another five at the speaker? It seems like simple addition, but I have a feeling it is more like complex multiplication.
Well, technically you can, but you are running into two main issues: headroom and phase. Let us talk about digital headroom first. In a digital system, there is a maximum volume level called zero decibels full scale. If you boost a frequency by five decibels at the server, and then boost it again by five decibels at the speaker, you are very likely to push that signal past the limit. When that happens, the top of the waveform gets chopped off. That is digital clipping, and it sounds like harsh, metallic distortion. But even more importantly, most traditional equalizers use what we call Infinite Impulse Response filters, or IIR filters. These filters work by delaying the signal and feeding it back into itself. This process inherently changes the phase of the sound.
Phase is one of those things that sounds like science fiction to most people. Can you explain it like I am five? Why does changing the phase make my podcast sound bad?
Think of a sound wave like a literal wave in the ocean. If you have two waves that hit at the exact same time, they combine to make a bigger wave. That is constructive interference. But if one wave is slightly delayed, the peak of one wave might hit the trough of the other, and they cancel each other out. That is destructive interference. When you stack multiple EQs, you are shifting the timing of different frequencies by tiny amounts. This creates "smearing." The transients—the sharp sounds like the letter T or K in speech—lose their impact. The audio feels hollow, or like it is moving around inside your head in an unnatural way. It is especially noticeable with voices, which is relevant for Daniel's podcast listening scenario.
That makes sense. If the timing of the speech gets smeared, it loses that crispness that makes it easy to understand. It is like the difference between someone speaking clearly and someone speaking through a thick curtain. So, if we want to avoid the lasagna, we need a hierarchy. In my mind, the first rule should be to pick one place to be the master of the frequency response. If you were setting this up today, with the current state of Home Assistant and Music Assistant two point zero, would you make the speaker the master or the network?
If I am using a system like Snapcast and Home Assistant, I am leaning heavily toward the network being the master. Here is why. When you use the built-in EQ on a consumer speaker, you are often at the mercy of whatever the manufacturer thought sounded good in a lab. But in a home automation environment, you have way more power. With Home Assistant and Music Assistant, you can use things like CamillaDSP. CamillaDSP is an incredibly powerful digital signal processing engine that can run on a Raspberry Pi or your main server. It allows for parametric equalization, which is much more precise than the basic bass and treble knobs on Daniel's Behringer speaker. You can target a very specific frequency—say, a resonance at one hundred and twenty hertz caused by a cabinet—and pull it down without affecting anything else.
So you are saying, turn those physical knobs to the middle, or what we call the flat position, and leave them alone forever? That sounds almost too easy. What about the "room correction" switches on the back of those Behringers? They usually have settings for "quarter space" or "half space" depending on if the speaker is against a wall or in a corner. Should Daniel ignore those too?
That is the one exception. Those hardware switches are designed to compensate for "boundary gain." When you put a speaker against a wall, the bass frequencies reflect off the wall and combine with the forward-firing sound, making it sound boomy. If Daniel knows that a speaker is going to live in a corner forever, using that hardware switch to cut the bass by two or four decibels is actually a good idea because it happens at the analog level before the amplifier. It preserves digital headroom. But once that is set, you should never touch it again. Set it for the physical location, then do all your "listening" adjustments in the software.
I see the appeal of the single pane of glass. But what about the room-specific issues we talked about? If the kitchen is too bright and the bedroom is too muffled, a single global EQ at the server level is not going to fix that. It might make the kitchen better but make the bedroom worse. If I am sitting in the living room and I think the podcast sounds a bit thin, I do not want to change the EQ for the whole house.
That is where the power of a tiered approach comes in. In a sophisticated setup, you have a global EQ for the "flavor" of the audio, and then you have a per-client EQ for "room correction." Snapcast is actually perfect for this because each client can have its own local configuration. In the Snapcast settings, you can define a specific command to process the audio before it plays. You can run a room measurement using a calibrated microphone—like a MiniDSP UMIK-one, which costs about one hundred dollars—and use a free tool called Room EQ Wizard, or REW. REW will look at the acoustic response of your kitchen and generate a "convolution filter."
A convolution filter? That sounds like something out of a math textbook. How does that differ from a regular EQ?
A regular EQ is like a scalpel; a convolution filter is like a 3D mold of the room's acoustics. It captures the echoes, the resonances, and the frequency dips. When you apply that filter to the Snapcast client in the kitchen, it essentially tells the speaker to play the "opposite" of the room's problems. If the room has a massive echo at two kilohertz, the filter cancels it out. This "flattens" the room. Once every room is flattened using these local filters, they all sound identical. Then, you can use Music Assistant to apply a single "Global EQ" that affects everything. If you want more bass for the whole house, you move one slider, and it sounds the same in every room.
That sounds like a lot of work for a podcast, Herman. I mean, I love our show, but do I need a calibrated microphone and convolution filters to hear you tell me about the history of the transistor? I can imagine Daniel's family wondering why he is standing in the middle of the kitchen with a microphone on a tripod while a speaker makes weird "whoop" noises for three hours.
Well, Daniel did say he likes the "more pure" or "technically correct" way of doing things! But you are right, for speech, the requirements are different than for critical music listening. For podcasts, the most important thing is the "intelligibility" of the human voice. Most human speech lives in the range between one hundred hertz and about four kilohertz. If you have too much low-end buildup from the room, the voice sounds "boomy" and hard to understand. If you have too much high-end reflection, it sounds "sibilant" and piercing. You do not necessarily need a convolution filter for that. You can use a simple parametric EQ at the client level.
So for Daniel's specific goal—listening to a podcast around the house—what is the "easy to maintain" version of this? Because walking around with a microphone feels like a weekend project that never ends, and we know how those go. We still have that half-finished smart mirror in the garage from twenty twenty-three.
The "easy to maintain" version is what I call the "Neutral Source, Local Trim" method. Step one: set all your speakers to their neutral or factory default settings. If they have an "Auto-EQ" feature like some modern smart speakers, turn it off for now so you can hear the baseline. Step two: use Music Assistant to create a "Speech" profile. This profile would have a gentle high-pass filter—maybe cutting everything below eighty hertz. This removes the "thump" from footsteps or microphone handling noise in the podcast. Then, add a slight boost in the "presence" range, around three kilohertz. This makes voices pop. Step three: if a specific room still sounds weird, you use the Home Assistant dashboard to tweak the "local" EQ for that specific Snapcast client.
I like that. It is a "set it and forget it" approach. But let's talk about the Apple technology Daniel mentioned. Apple uses the microphones in the HomePod to automatically sense the room and adjust the EQ in real-time. It uses the A-series chips to do billions of calculations a second. That seems like the dream, right? No microphones, no manual filters, just "smart" audio. Why can we not do that with Home Assistant? We have the processing power.
We actually can, but it is much harder because we do not have the integrated hardware. Apple has the advantage of knowing exactly where the microphone is in relation to the speaker drivers. They can send out a "chirp," listen to the reflection, and calculate the room's impulse response in seconds. They even use the woofer's back-electromotive force to sense how the air in the room is resisting the speaker cone. For us to do that with a DIY setup, we would need a microphone connected to every Snapcast client, and some pretty beefy code to process that data in real-time. There are some projects like "AutoEQ" for headphones, but for rooms, it is still the "holy grail" of DIY audio. For now, manual tuning is still more reliable because you can use your own ears as the final judge.
It is interesting that you mention the "chirp." I have noticed that some of the newer high-end receivers are doing this now with mobile apps. You just stand in the middle of the room with your phone, it plays some weird space noises, and then suddenly the system sounds twice as good. It feels like magic, but it is just mathematics. It is calculating the "transfer function" of the room. Every room is essentially a big, complex filter. It adds its own EQ to whatever you play. Room correction is just an "inverse filter."
Exactly. If the room adds three decibels at two hundred hertz, the room correction subtracts three decibels at two hundred hertz. The goal is a flat line. But here is the catch: you can only fix frequency, you cannot fully fix time. If your room has a three-second reverb because it is all glass and concrete, no amount of EQ is going to make it sound like a recording studio. You have to be realistic about what DSP can do. It can fix the "tone," but it cannot fix the "space."
So, if Daniel is using a mix of speakers—he mentioned a Behringer PA speaker and a Bluetooth speaker connected via an adapter—he is dealing with very different "native" sounds. The Behringer is probably quite mid-forward and loud, while a small Bluetooth speaker might be struggling to produce any bass at all. If he manages EQ on the network, can he actually make those two very different speakers sound similar? Or is he always going to notice the transition?
To a point, yes. And this is actually one of the strongest arguments for doing it in Home Assistant. You can create a "profile" for each specific hardware type. You could have a "Behringer Profile" that tames its aggressive mids, and a "Bluetooth Speaker Profile" that adds a bit of a "loudness" curve—boosting the lows and highs to make it sound fuller at lower volumes. This is a concept called "Target Curves." Instead of trying to make every speaker "flat," you try to make every speaker match a specific "house sound." By the time the audio reaches the clients, you have compensated for the weaknesses of the hardware. Then, on top of that, you have your room correction. It is like layers of a protective suit, each one handling a different threat to your audio quality.
I think the "consistency" part of Daniel's question is the most important for the user experience. There is nothing more jarring than walking from a room with a lot of bass into a room that sounds thin. It actually makes you feel like the audio is "breaking," even if it is perfectly synced. Our brains are very sensitive to changes in frequency response. If the "tonal balance" shifts as you move, your brain has to re-process what it is hearing, which is fatiguing. For a podcast, you want to be able to follow the thread of the conversation without your brain being distracted by the fact that the host suddenly sounds like they are speaking through a megaphone.
That fatigue is real. It is called "listener fatigue," and it usually comes from high-frequency distortion or phase issues. If Daniel sets up his system with a centralized DSP, he can ensure that the "crossover" between rooms is seamless. One thing he should look into is the "Music Assistant" integration for Home Assistant. As of the latest updates in twenty twenty-five, Music Assistant has a very robust DSP pipeline. It allows you to define "Player Groups" and apply an EQ to the entire group. So if he has a "Downstairs" group, he can tune that group to sound consistent, even if it contains three different brands of speakers.
Let's talk about the "easy to maintain" part. If Daniel adds a new speaker next month, what is his workflow in this "technically correct" system? I do not want him to have to spend four hours every time he buys a new gadget. I know I certainly do not want to do that.
If he has it set up the way we are discussing, the workflow is beautiful. He plugs in the new speaker. He sets its physical knobs to flat. He adds it to Snapcast. In Home Assistant, he assigns it a profile. If it is a small speaker, he gives it the "Small Speaker" profile which has a built-in bass protection filter. He listens for a minute. If it sounds a bit boomy in its new spot, he tweaks the low-end slider for that specific client in the Home Assistant dashboard. Done. He does not have to worry about whether he changed the EQ in the source app, or in the speaker's proprietary app, or on the back of the speaker itself. It is a single source of truth.
That sounds much better than the "hunt and peck" method of trying to find which app is currently controlling the volume and tone. I have been there, where I am trying to turn down the bass and I realize I have three different EQs active and I do not know which one is the culprit. It is a nightmare. And it is a great lesson in system design: complexity should be centralized, and endpoints should be as simple as possible. In the world of enterprise networking, we call this "thin clients." The speaker is just a "thin client" for the audio. The "fat server"—Home Assistant—does all the thinking.
Exactly. And let's address the specific "weird sounding output" Daniel mentioned when layering. Is there a specific "tell" or a symptom that listeners can look out for that indicates they have too much EQ stacking? Yes! Look for "phaseiness." If the audio starts to feel like it is moving around in your head, or if the center image of a voice feels like it is "smeared" or coming from nowhere in particular, you probably have phase issues from stacked filters. Another one is "pumping" or "breathing." If you have a compressor or a "smart" EQ at the speaker level and then another one at the network level, they can start fighting each other. One tries to turn the volume up while the other tries to turn it down. It creates this unstable, wavering sound that is very fatiguing to listen to.
I have heard that before! It sounds like the audio is gasping for air. Okay, so we have a clear recommendation for Daniel: centralize the DSP in Home Assistant, keep the speakers flat, and use Snapcast's per-client capability for room-specific tweaks. But I want to push back on one thing. What about latency? Daniel mentioned that Snapcast has "almost perfect latency." If we start adding heavy digital signal processing like convolution filters in Home Assistant, are we going to break that sync? I know that some of those FIR filters require a lot of "taps," and that takes time to process.
That is a very sharp question, Corn. And the answer is: it depends on how you do it. Most basic EQs—parametric or graphic—have negligible latency. We are talking about a few samples, which is a fraction of a millisecond. You will never hear it. However, if you use "Linear Phase" FIR filters for room correction, those can introduce significant latency—sometimes fifty or even a hundred milliseconds. If the kitchen is a hundred milliseconds behind the living room, it is going to sound like a weird echo chamber. You will feel like you are losing your mind.
Oh, that would definitely break the sync. So how do the pros handle it? If I want the high-quality filter but I also want the sync, what is the fix?
There are two ways. First, you can use "Minimum Phase" filters instead of "Linear Phase." They have much lower latency but can introduce some of that phase shifting we talked about. For most home users, this is the best compromise. Second, the "pro" move is to ensure that the latency is the same across all clients. If one client needs fifty milliseconds of processing time, you add a fifty-millisecond delay to all the other clients so they stay in sync. Snapcast actually has a setting for this called "latency offset." You can manually tune the delay for each client to account for the processing time. It is a one-time calibration. You play a "click" track through all the speakers, and you adjust the offsets until all the clicks happen at the exact same time.
This is where it starts to feel like a full-time job again, Herman. But I suppose once you have those offsets dialed in, they do not really change unless you change your hardware. For Daniel's podcast setup, he is probably not going to need massive convolution filters anyway. A simple parametric EQ in Music Assistant will do ninety percent of the work with zero latency.
Exactly. For speech, you really do not need to go overboard. One thing I would recommend for Daniel is to look at the "Loudness" standard, specifically EBU R one hundred and twenty eight. It is a standard for consistent volume levels. Music Assistant can actually normalize the volume of different podcasts so that one is not screaming at you while the other is a whisper. This, combined with a good EQ, makes for a much more professional listening experience. It is the kind of thing that makes you feel like you are living in the future.
Let's talk about the "Music Assistant" part of this. For those who are not deep in the Home Assistant ecosystem, Music Assistant is a relatively new and very powerful integration that acts as a "music boss" for your whole house. It can pull in Spotify, local files, radio stations, and podcasts, and then pipe them out to various "players," including Snapcast. Does Music Assistant make this EQ management easier? I have seen the new dashboard they released late last year, and it looks pretty slick.
It does, because Music Assistant is designed to be the "source of truth." It has a built-in EQ engine that applies to the stream before it even hits the Snapcast server. So, if you want that "Speech" profile we talked about, you set it up in Music Assistant. This is great because it means no matter which room you turn on, or how many rooms you group together, that "voice-optimized" sound is baked into the stream. It is the ultimate "global flavor" layer. And because it is integrated with Home Assistant, you can automate it. You could have a "Morning Podcast" automation that turns on the kitchen and bathroom speakers, sets the volume to thirty percent, and applies the "Speech" EQ. Then, in the evening, when you want to listen to music, it switches to a "Music" EQ with more bass and treble.
So, if I am Daniel, I set my "Speech" EQ in Music Assistant, I leave my Snapcast clients "flat" unless a room is particularly problematic, and I leave the physical speakers "flat." That seems like a very clean, three-tier system. It avoids the lasagna because each layer has a specific, non-overlapping job. Layer one is hardware neutrality. Layer two is room correction. Layer three is content optimization.
That is the perfect summary. And it is robust. If Daniel's wife or a guest wants to use the system, they do not need to know about the EQs. They just use the Home Assistant dashboard to play a podcast, and the "magic" happens behind the scenes. That is the "easy to maintain" part. You build the complexity into the architecture so that the day-to-day use is simple. It is about "intentionality." Do not let your hardware make decisions for you. You should decide how you want your house to sound, and then use your tools to achieve that.
I think there is a broader lesson here about "digital hygiene" in our homes. We are increasingly surrounded by "smart" devices that all want to "help" us by processing our audio, our video, and our data. But when you have ten "helpful" devices all processing the same thing, they end up getting in each other's way. Whether it is motion smoothing on a television or auto-EQ on a speaker, often the best thing you can do is turn it all off and pick one single, high-quality place to do the work. It is like having too many cooks in the kitchen—everyone is adding salt, and eventually, the soup is inedible.
I couldn't agree more. The "technically correct" way is usually the one that gives you the most control and the most transparency. If you have a high-quality speaker like those Behringers, they are capable of incredible sound, but they need a clean signal. If you feed them a signal that has already been mangled by three different software EQs, they are just going to accurately reproduce a mangled signal.
Let's touch on one more thing before we wrap up. Daniel mentioned the Apple technology using AI to create an optimized EQ. We are seeing more of this "AI-driven" audio correction. There are even some VST plugins now that claim to use machine learning to "un-mix" a room's acoustics. Do you think we are heading toward a world where we won't need to worry about any of this? Where the "network" will just know what kind of speaker is connected and what the room sounds like?
We are definitely heading there. There are already protocols like "Device Description" where a speaker can tell the network its make, model, and frequency response curve. Imagine a future version of Snapcast where, as soon as you plug in a Behringer speaker, Home Assistant downloads the "official" correction curve for that model and applies it automatically. Then, using the microphone on your phone or a dedicated sensor, it does a quick "room ping" and fine-tunes it. We are probably only a few years away from that being a standard feature in the open-source world. In fact, some people are already doing this with "AutoEQ" databases for headphones. They have measured thousands of headphones and created "perfecting" filters for all of them. Doing that for speakers in a room is just the next logical step.
That would be incredible. It would democratize high-fidelity audio. You wouldn't need to be a "Herman Poppleberry" to have a house that sounds like a professional studio. You could just plug it in and let the AI handle the physics. But until then, I guess we are stuck with the manual way.
Hey, I'm happy to be put out of a job if it means everyone gets better audio! But until then, a little bit of manual tinkering and a solid architectural philosophy go a long way. And honestly, there is a certain satisfaction in finally getting that kitchen speaker to sound just right after weeks of it sounding like a tin can. It is the tinkerer's reward.
Well, I think we have given Daniel a lot to chew on. To summarize: aim for a "flat" foundation at the hardware level, centralize your "flavor" EQ in Music Assistant or Home Assistant, and use per-client correction only where the room physics absolutely demand it. Avoid the "EQ Lasagna" at all costs. And if you are feeling brave, get a calibrated microphone and learn the basics of Room EQ Wizard. It is a rabbit hole, but it is a fun one.
And if you can, use parametric EQ instead of graphic EQ. It is much more powerful for surgical corrections, like removing a specific "boom" in a room without affecting the rest of the bass. A graphic EQ is like a blunt instrument; a parametric EQ is like a laser. Most modern Home Assistant integrations support parametric EQ now, so there is no reason not to use it.
Great tip. Well, this has been a fascinating deep dive. I feel like I need to go home and check the settings on my own speakers now. I think I might have a bit of a "lasagna" situation developing in the guest room.
You and me both, Corn. I think I noticed a bit of a mid-range bump in the hallway this morning. I might have to break out the UMIK-one this weekend and do some fresh measurements.
Of course you did. Well, before we go, I want to say a big thank you to Daniel for sending in this prompt. It is exactly the kind of "weird" technical puzzle we love to solve. If you out there are enjoying these deep dives into the intersection of technology and daily life, we would really appreciate it if you could leave us a review on your favorite podcast app. Whether it is Spotify, Apple Podcasts, or anywhere else, those ratings really help new people find the show. We are trying to reach more people who care about the "why" behind their gadgets.
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This has been My Weird Prompts. Thanks for joining us in our corner of Jerusalem. It is a beautiful day here, and I hope it is a beautiful day wherever you are listening.
Until next time, keep your signals clean and your sync tight. Goodbye!
Goodbye everyone!
