6 Prompts for Podcast Audio Engineering Notes

Introduction (~300 words)

Ever hit “record” on your podcast, only to cringe when you play it back? Maybe the volume jumps between speakers, or long silences make the conversation feel awkward. Poor audio quality isn’t just annoying—it can make listeners click away in seconds. Studies show that 50% of podcast listeners will stop listening if the audio is bad, even if the content is great. That’s why audio engineering matters. It turns raw recordings into polished, professional-sounding episodes that keep people coming back.

But here’s the good news: you don’t need a fancy studio or years of experience to fix these problems. AI tools are changing the game for podcasters. With just a few simple prompts, you can remove silence, balance volume levels, and even clean up background noise—all in minutes. No more spending hours tweaking EQ settings or guessing which effects to use. These tools do the heavy lifting, so you can focus on what really matters: your content.

This guide will walk you through six essential prompts for AI audio engineering. Whether you’re a beginner just starting out or a pro looking to save time, these tips will help you get better results with less effort. We’ll cover:

• How to remove awkward silences automatically
• The best way to normalize volume for a smooth listen
• Simple EQ tricks to make voices sound clear and natural
• Which AI tools work best (and how to use them)

The best part? You don’t need to be a tech expert. These prompts are designed to be easy to follow, even if you’ve never edited audio before. And with AI handling the technical stuff, you’ll get consistent, professional-quality results every time—without the headache. Ready to make your podcast sound its best? Let’s dive in.

Understanding the Basics of Podcast Audio Engineering

Great podcast audio isn’t just about having a good microphone. It’s about making sure your listeners can hear you clearly, without distractions. Think about the last time you listened to a podcast where the host’s voice kept fading in and out, or there was a loud hum in the background. Frustrating, right? That’s why audio engineering matters—it turns raw recordings into polished, professional-sounding episodes.

The core of good podcast audio comes down to four key things: clarity, volume consistency, noise reduction, and EQ balance. Clarity means your voice sounds natural, not muffled or distant. Volume consistency keeps your voice at the same level, so listeners don’t have to constantly adjust their volume. Noise reduction removes unwanted sounds like fans, traffic, or that annoying echo in your room. And EQ (equalization) balances the frequencies in your voice, making it sound full and pleasant instead of tinny or boomy.

Common Audio Problems (And Why They Happen)

Even the best microphones can’t fix everything. Here are some of the most common issues podcasters face:

• Plosives – Those loud “p” and “b” sounds that create a popping noise. They happen when air hits the microphone too hard.
• Sibilance – Harsh “s” and “sh” sounds that can be painful to listen to. Some voices naturally have more sibilance than others.
• Background noise – Fans, air conditioners, or even outside traffic can sneak into your recording.
• Inconsistent volume – If you move around while talking, your voice might get louder or softer without you realizing it.

These problems don’t just make your podcast sound unprofessional—they can make it hard for listeners to stay engaged. Imagine trying to follow a story while constantly adjusting your volume or straining to hear over background noise. Most people won’t bother—they’ll just hit “stop” and move on to the next podcast.

Why Manual Editing Takes So Much Time

Traditional audio editing in programs like Audacity or Adobe Audition can feel like solving a puzzle. You have to:

• Cut out silences – Listening through long pauses and manually removing them.
• Normalize volume – Adjusting levels so the loudest and quietest parts sound balanced.
• Apply EQ – Tweaking frequencies to make voices sound natural.
• Remove noise – Using tools to clean up background hums or echoes.

For a 30-minute episode, this can take hours—especially if you’re new to audio editing. And if you’re not careful, you might accidentally make things worse. Ever heard a podcast where the host’s voice sounds robotic or unnatural? That’s usually the result of over-editing.

How AI Makes Audio Engineering Easier

AI tools are changing the game for podcasters. Instead of spending hours tweaking settings, you can now use simple prompts to:

• Remove silence automatically – No more manually cutting out pauses.
• Normalize volume – The AI adjusts levels so your voice stays consistent.
• Clean up noise – Background hums and echoes disappear with one click.
• EQ voices – The AI analyzes your voice and applies the best settings.

The best part? You don’t need to be a tech expert. These tools do the hard work for you, so you can focus on creating great content. But does that mean AI can replace human audio engineers entirely?

AI vs. Human Audio Engineers: When to Use Each

AI is fast, affordable, and great for repetitive tasks. If you’re just starting out or need quick results, it’s a fantastic option. But there are times when a human touch still makes a difference.

When to use AI:

• You’re on a tight budget.
• You need quick, consistent results.
• Your audio issues are simple (background noise, volume inconsistencies).

When to hire a professional:

• Your recording has complex issues (bad room acoustics, multiple speakers with different mics).
• You want a custom sound (like a branded podcast intro/outro).
• You’re producing high-budget content and need top-tier quality.

Think of AI like a smart assistant—it can handle the boring, repetitive work, but it’s not a replacement for a skilled human. The good news? You don’t have to choose one or the other. Many podcasters use AI for the heavy lifting and then fine-tune the results themselves.

At the end of the day, great podcast audio isn’t about having the most expensive gear. It’s about making sure your listeners can hear you clearly, without distractions. And with the right tools, you can achieve that—even if you’re not an audio expert.

Prompt 1: Removing Silence and Dead Air

Silence might be golden in some situations, but in podcasts? Not so much. Long pauses and dead air can make your episode feel slow, awkward, or even unprofessional. Think about it—when was the last time you kept listening to a podcast where the host took five seconds to respond to a question? Most listeners won’t wait that long. Studies show that if a podcast has more than three seconds of silence, drop-off rates can jump by up to 30%. That’s a lot of potential fans clicking away before you even get to the good stuff.

The problem isn’t just about losing listeners, though. Silence disrupts the flow of your content. A great podcast should feel like a natural conversation, not a series of stilted exchanges. When there’s too much dead air, it breaks the rhythm and makes it harder for listeners to stay engaged. Even if your content is amazing, those awkward pauses can make it feel less polished. The good news? Fixing this is easier than you think—especially with AI tools.

Why Silence Removal Matters More Than You Think

Let’s be real: no one records a perfect take. Even the most experienced podcasters need to pause, gather their thoughts, or take a breath. But those pauses add up. A 30-minute episode can easily turn into 40 minutes of raw audio, filled with unnecessary gaps. Removing silence doesn’t just tighten your episode—it makes it more engaging. Listeners are more likely to stick around when the pacing feels natural and dynamic.

Here’s the thing: silence removal isn’t about cutting out every single pause. Some silences are intentional—like dramatic pauses in storytelling or moments of reflection. The key is finding the right balance. Too much silence? Your podcast feels slow. Too little? It sounds rushed and unnatural. The goal is to keep the conversation flowing while preserving the natural rhythm of speech.

How to Craft the Perfect AI Prompt for Silence Removal

So, how do you tell an AI tool to remove silence without making your podcast sound robotic? It’s all about the prompt. You need to be specific about what you want. Here’s what to include:

• Threshold: How quiet does a pause need to be to count as silence? (e.g., -30dB)
• Minimum duration: How long should a pause be before it gets cut? (e.g., 0.5 seconds)
• Fade-in/out: Should the tool add a smooth transition between cuts? (e.g., 100ms fade)

A good example of a prompt might look like this: “Remove all silences longer than 0.5 seconds with a 100ms fade-in and fade-out. Keep natural pauses in storytelling but cut unnecessary dead air.”

This tells the AI exactly what to do while leaving room for context. Some tools, like Descript, even let you adjust these settings manually after the AI does its initial pass. That way, you can fine-tune the results to sound just right.

Tools That Make Silence Removal a Breeze

Not all AI tools handle silence removal the same way. Some are better at preserving natural speech, while others focus on speed. Here are a few options to consider:

• Descript: Great for beginners. Its “Remove Filler Words” feature also cuts out “ums” and “uhs,” making your audio even cleaner.
• Auphonic: More advanced. It uses “Smart Leveling” to balance audio levels while removing silence, which is perfect if you’re dealing with multiple speakers.
• Adobe Podcast: Simple and effective. It automatically detects and removes silence while keeping the conversation natural.

One podcaster I know used Descript to remove silence from their episodes and saw a 20% reduction in runtime—without losing any key content. That’s 20% less dead air and 20% more engagement. Not bad for a few clicks!

Common Mistakes to Avoid

Silence removal is powerful, but it’s easy to overdo it. Here are a few pitfalls to watch out for:

• Over-aggressive cuts: If you set the minimum duration too low (e.g., 0.2 seconds), the AI might cut out natural breathing or short pauses, making your speech sound choppy.
• Ignoring context: Some silences are intentional. If you’re telling a story, a well-placed pause can add drama. Don’t let the AI strip those out.
• No manual review: Always listen to the edited version. AI isn’t perfect, and sometimes it cuts things it shouldn’t.

The best approach? Start with conservative settings, then adjust as needed. You can always run the tool again if you’re not happy with the results.

Final Thoughts

Removing silence is one of the easiest ways to make your podcast sound more professional. It tightens your pacing, keeps listeners engaged, and saves you time in editing. The key is to use the right tools and settings—without going overboard. Try experimenting with different prompts and see what works best for your style. Your listeners will thank you!

Prompt 2: Normalizing Audio Levels for Consistency

Ever listened to a podcast where the host’s voice suddenly drops to a whisper, then blasts back at full volume? It’s like riding a rollercoaster—except instead of fun, you’re just annoyed. Inconsistent audio levels are one of the biggest frustrations for podcast listeners. One minute, you’re straining to hear a quiet guest. The next, you’re scrambling to turn down the volume because the host just laughed too loudly. It’s exhausting, and most listeners won’t stick around for it.

The good news? This problem is completely fixable—without spending hours tweaking volume sliders. Normalizing audio levels means adjusting the loudness of your entire episode so it sounds consistent from start to finish. Think of it like setting the cruise control for your podcast’s volume. No more sudden jumps, no more awkward silences where you can’t hear anything. Just smooth, professional-sounding audio that keeps listeners engaged.

Why LUFS Matters More Than You Think

If you’ve ever wondered why some podcasts sound louder or quieter than others, the answer is LUFS (Loudness Units Full Scale). This is the industry standard for measuring audio loudness, and it’s what streaming platforms like Spotify and Apple Podcasts use to balance volume across different shows. The magic number for podcasts? -16 LUFS. This is the sweet spot that keeps your audio loud enough to hear clearly, but not so loud that it distorts or feels unnatural.

Here’s a quick breakdown of LUFS targets for different podcast formats:

• Interview podcasts: -16 LUFS (standard for most shows)
• Solo episodes: -14 to -16 LUFS (slightly louder to compensate for single voice)
• Narrative/storytelling podcasts: -18 to -20 LUFS (more dynamic range for dramatic effect)
• Live recordings: -14 LUFS (to account for background noise and varying mic distances)

Why does this matter? Because if your podcast is too quiet, listeners will turn up the volume—and then get blasted by the next show that’s too loud. If it’s too loud, streaming platforms might automatically turn it down, making your audio sound muffled. Sticking to -16 LUFS ensures your podcast plays nicely with others in the feed.

How to Write the Perfect Normalization Prompt

The key to getting great results from AI audio tools is giving clear, specific instructions. Here’s an example of a strong normalization prompt:

“Normalize the audio to -16 LUFS with a true peak of -1 dB. Ensure consistent loudness across all speakers, and avoid over-compression. If there are sudden volume changes (like laughter or loud breaths), smooth them out without making the audio sound unnatural.”

This prompt does a few important things:

1. Sets a target LUFS value (-16 LUFS is the standard for podcasts).
2. Limits the true peak (-1 dB prevents distortion).
3. Balances multiple speakers (critical for interview shows).
4. Handles dynamic moments (like laughter or coughs) without over-correcting.

If you’re using a tool like Auphonic, it will automatically adjust levels while preserving the natural dynamics of speech. Adobe Podcast’s “Enhance Speech” takes a different approach—it uses AI to clean up audio first, then normalizes it. Both work well, but Auphonic is better for multi-speaker shows, while Adobe Podcast shines for solo episodes with background noise.

Before and After: The Power of Normalization

Let’s say you record an interview where the guest’s mic is too quiet, and the host’s voice is too loud. Without normalization, the episode sounds like this:

• Host: “So tell me about your new book!” (loud, clear)
• Guest: “Well, it’s about…” (barely audible, you strain to hear)
• Host: “That sounds amazing!” (suddenly too loud again)

After normalization, the same clip sounds like this:

• Host: “So tell me about your new book!” (balanced, natural)
• Guest: “Well, it’s about…” (now clearly audible)
• Host: “That sounds amazing!” (same volume as before)

The difference is night and day. Listeners can focus on the conversation instead of constantly adjusting their volume. And the best part? You didn’t have to manually tweak every single clip.

Advanced Tips for Multi-Speaker Podcasts

Normalizing a solo episode is straightforward, but things get trickier when you have multiple speakers. Here’s how to handle it:

1. Use per-speaker normalization: Some AI tools (like Descript) let you normalize each speaker’s audio separately. This is great for interviews where one person’s mic is quieter than the other.
2. Watch for compression artifacts: If you normalize too aggressively, voices can start to sound “squashed” or robotic. A good rule of thumb is to keep the dynamic range (the difference between loud and quiet parts) as natural as possible.
3. Handle live recordings differently: If you’re recording a live show or panel discussion, expect more background noise and uneven mic levels. In this case, aim for -14 LUFS to compensate for the extra noise, and use a noise gate to clean up silent moments.

Normalization isn’t just about making your podcast louder—it’s about making it consistent. When every episode sounds the same, listeners know what to expect, and they’re more likely to hit “subscribe.” And with AI tools doing the heavy lifting, you don’t need to be an audio expert to get it right. Just set your target LUFS, let the AI work its magic, and enjoy the results. Your listeners will thank you.

Prompt 3: EQ (Equalization) for Clearer Voices

Ever listen to a podcast where the host’s voice sounds muffled, too boomy, or just hard to understand? That’s usually an EQ problem. Equalization (EQ) is like a magic tool that shapes how voices sound—cutting the bad frequencies and boosting the good ones. It’s the secret weapon that makes professional podcasts sound so crisp and clear. And the best part? You don’t need to be an audio engineer to use it. With the right AI tools and a simple prompt, you can fix common voice issues in minutes.

Why EQ Matters for Podcasts

Think of EQ like adjusting the bass and treble on a car stereo, but way more precise. A good EQ can:

• Remove muddiness (that “underwater” sound when voices get lost in low frequencies)
• Reduce harshness (sharp, tiring high frequencies that make listeners reach for the volume knob)
• Add warmth and clarity (so voices sound natural, not thin or robotic)

Without EQ, even the best microphones can sound bad. A cheap mic with proper EQ will often beat an expensive one with no EQ at all. That’s how powerful it is.

Common Voice Problems and How to Fix Them

Every voice is different, but most podcasts struggle with the same few issues. Here’s what to listen for and how to fix it:

• Muddiness (200-500Hz) – Too much here makes voices sound boxy or unclear. A gentle cut (3-4dB) in this range cleans things up.
• Harshness (2-5kHz) – This is where “s” sounds and sharp tones live. If it’s too much, voices sound fatiguing. A small cut (1-2dB) helps.
• Thinness (lack of 100-300Hz) – Voices sound weak or distant. A slight boost here adds fullness.
• Boominess (80-150Hz) – Deep voices can sound too “rumble-y.” A high-pass filter (cutting below 80Hz) removes unwanted low-end noise.

A good starting prompt for AI tools might look like this: “Apply a gentle high-pass filter at 80Hz, boost 2-5kHz by 2dB for clarity, and cut 300-500Hz by 3dB to reduce muddiness.”

AI Tools That Can Handle EQ

Not all AI audio tools are equal when it comes to EQ. Some just apply basic presets, while others let you tweak settings like a pro. Here’s what to look for:

• Descript’s “Studio Sound” – Great for beginners. It automatically cleans up voices but doesn’t let you adjust EQ manually.
• iZotope RX – More advanced. You can see frequency issues visually and fix them with precision.
• Adobe Podcast Enhance – Simple but effective. It applies EQ and noise reduction in one click.

If you’re just starting, try an AI preset first. Once you get comfortable, experiment with custom settings. For example, deep voices might need less low-end cut, while high-pitched voices could use a slight boost in the mids.

EQ for Different Voices

Not all voices need the same EQ. A deep, resonant voice might sound great with just a high-pass filter, while a thin or nasal voice could use a boost around 1-3kHz. Accents can also change how EQ works—some languages emphasize different frequencies.

Case Study: A podcast with non-native English speakers struggled with clarity. After testing, they found that cutting 400Hz and boosting 3kHz made a huge difference. Listeners reported understanding the hosts much better, and engagement went up.

Final Tip: Less Is More

EQ is powerful, but it’s easy to overdo it. If you boost too much in one area, voices can sound unnatural. Start with small adjustments (1-3dB) and listen carefully. The goal is to make voices clearer, not “perfect.”

With the right prompt and a little practice, EQ can take your podcast from amateur to professional in no time. Try it on your next episode and hear the difference!

Prompt 4: Noise Reduction and Background Cleanup

Ever listened to a podcast where the host sounds like they’re recording from inside a wind tunnel? Or maybe there’s a constant hum in the background that makes you want to reach for the volume knob? Background noise is the silent killer of podcasts—it distracts listeners, makes your content feel unprofessional, and can even drive people away before they hear your message.

The truth is, no matter how great your microphone is, noise will find a way in. Maybe it’s the hum of your computer fan, the distant sound of traffic outside, or the echo of your voice bouncing off bare walls. These little distractions add up, pulling your listener’s attention away from what you’re saying. And in a world where people have endless options for content, you can’t afford to lose them over something as fixable as background noise.

Why Noise Matters More Than You Think

Think about the last time you struggled to hear someone in a noisy café. You probably leaned in, focused harder, and maybe even asked them to repeat themselves. Now imagine your listeners doing that for your entire podcast. It’s exhausting—and most people won’t bother. Studies show that even small amounts of background noise can reduce comprehension by up to 30%. That means your audience isn’t just hearing the noise—they’re missing parts of your message.

Common noise culprits include:

• HVAC systems (that constant low rumble)
• Computer fans (especially if your mic is close to your setup)
• Traffic or outdoor sounds (if you’re recording near a window)
• Echo or reverb (from recording in an empty room)
• Electrical hum (from cheap cables or power sources)

The good news? Most of these can be fixed with the right tools and a well-written prompt.

Writing an AI Prompt for Noise Reduction

AI tools are great at cleaning up audio, but they need clear instructions. A vague prompt like “Remove noise” won’t cut it—you need to tell the AI exactly what kind of noise to target and how aggressive to be. Here’s how to write an effective prompt:

1. Specify the noise type – Is it hiss, hum, fan noise, or something else?
2. Set the reduction level – Do you want it gone completely, or just reduced by 80%?
3. Protect the voice – Always include a note like “without affecting voice quality” to avoid robotic-sounding results.

Example prompt: “Remove background hiss and reduce ambient room noise by 80% without affecting voice quality. Preserve natural speech dynamics and avoid over-processing.”

This tells the AI to focus on the right frequencies while keeping your voice sounding human. Some tools, like Adobe Podcast’s “Noise Reduction,” even let you adjust settings after the AI does its initial pass, so you can fine-tune the results.

AI Tools for Noise Reduction: Which One Should You Use?

Not all noise reduction tools are created equal. Here’s a quick breakdown of the best options:

• Krisp – Best for live calls and real-time noise removal. Great if you’re recording interviews over Zoom or Discord.
• Adobe Podcast’s “Noise Reduction” – Simple and effective for post-production. Just upload your file and let the AI do the work.
• iZotope RX – The gold standard for professionals. More advanced (and expensive), but can handle complex noise like overlapping voices or music.

For most podcasters, Adobe Podcast or Krisp will be enough. But if you’re dealing with tricky noise—like a fan that speeds up and slows down—iZotope RX might be worth the investment.

When to Use AI vs. Manual Noise Reduction

AI is fantastic for quick fixes, but it’s not perfect. If your recording has:

• Overlapping voices (like in a group discussion)
• Music or sound effects (which AI might mistake for noise)
• Extreme echo or reverb (which may need manual EQ adjustments)

…you might need to roll up your sleeves and do some manual editing. Tools like Audacity or Adobe Audition let you select noise profiles and apply reductions more precisely. But for most solo podcasters, AI will get you 90% of the way there with minimal effort.

Final Thought: Noise Reduction Is Worth the Effort

Clean audio isn’t just about sounding professional—it’s about respecting your listener’s time. When your podcast is free of distractions, people can focus on what you’re saying, not the hum of your air conditioner. And with AI tools making noise reduction easier than ever, there’s no excuse for letting background noise ruin your episodes.

Try running your next recording through an AI noise reducer and listen to the difference. Your audience will thank you.

Prompt 5: Compression for Smoother Audio

Ever listen to a podcast where one sentence is too loud, the next too quiet, and you’re constantly adjusting the volume? That’s what happens when audio isn’t compressed properly. Compression is like a volume manager—it evens out the loud and soft parts so your listeners don’t have to keep reaching for the volume knob. For podcasters, it’s one of the most important tools to make your show sound polished and professional.

But here’s the thing: compression isn’t just about making everything louder. It’s about control. Think of it like a bouncer at a club—it lets the quiet parts in but keeps the loud parts from getting out of hand. Without compression, your voice might sound uneven, with sudden spikes that distract listeners. With too much compression, your audio can sound flat and lifeless. The key is finding the right balance.

Compression vs. Normalization: What’s the Difference?

A lot of people confuse compression with normalization, but they do different things. Normalization makes your entire audio file louder by bringing the peak volume to a set level (like -1 dB). It doesn’t change the dynamics—just the overall loudness. Compression, on the other hand, actively reduces the volume of loud parts while leaving quieter parts alone (or even boosting them slightly). This creates a more consistent listening experience.

For example, if you’re recording an interview and one guest speaks softly while the other is booming, normalization won’t fix the difference between them. Compression will. That’s why most professional podcasts use both—normalization to set the overall loudness and compression to smooth out the dynamics.

How to Craft the Perfect Compression Prompt for AI

If you’re using an AI tool to handle your audio editing, you’ll need to give it clear instructions for compression. Here’s what to include in your prompt:

• Threshold (-20dB to -30dB): This tells the AI when to start compressing. A lower threshold (like -30dB) means it will compress more of the audio, while a higher threshold (like -20dB) only affects the loudest parts.
• Ratio (2:1 to 4:1): This determines how much the loud parts get turned down. A 2:1 ratio is gentle, while 4:1 is more aggressive.
• Attack (5ms to 30ms): How quickly the compressor reacts to loud sounds. A faster attack (5ms) clamps down immediately, while a slower attack (30ms) lets some natural dynamics through.
• Release (50ms to 300ms): How long the compressor takes to stop reducing volume after the loud part ends. A shorter release (50ms) can sound unnatural, while a longer release (200ms+) sounds smoother.

Here’s an example of a well-crafted prompt: “Apply light compression with a 4:1 ratio, -20dB threshold, 10ms attack, and 100ms release. Keep the audio natural—don’t squash the dynamics too much.”

AI Tools That Handle Compression Well

Not all AI audio tools are created equal when it comes to compression. Some do a great job, while others can make your audio sound worse if you’re not careful. Here are a few worth trying:

• Auphonic: Uses adaptive compression that adjusts based on your audio. Great for interviews where volume levels vary a lot.
• Descript’s “Studio Sound”: Combines noise reduction and compression in one step. Works well for solo shows but can sound a bit over-processed if you’re not careful.
• Adobe Podcast: Offers manual compression controls after the AI does its initial pass, so you can fine-tune the results.

The best tool depends on your needs. If you’re doing a solo show, Descript might be enough. For interviews or panel discussions, Auphonic’s adaptive compression is a lifesaver.

Avoiding Over-Compression: The “Pumping” Problem

One of the biggest mistakes podcasters make is over-compressing their audio. When compression is too aggressive, you get something called “pumping”—where the volume suddenly drops after a loud sound, making the audio sound unnatural. It’s like someone is constantly turning the volume knob up and down.

To avoid this:

• Start with a gentle ratio (2:1 or 3:1) and adjust from there.
• Keep the threshold around -20dB to -25dB unless your audio is extremely dynamic.
• Listen for distortion—if your voice starts sounding “crunchy,” you’ve gone too far.

Compression for Different Podcast Formats

Not all podcasts need the same compression settings. Here’s how to adjust for different formats:

• Solo shows: You can be a little more aggressive with compression since there’s only one voice to manage. A 3:1 or 4:1 ratio works well.
• Interviews: Use lighter compression (2:1 or 3:1) to preserve natural dynamics between speakers. Auphonic’s adaptive compression is great here.
• Panel discussions: These are the trickiest because multiple voices mean more volume spikes. Start with a 2:1 ratio and adjust as needed.
• Dynamic content (laughter, shouting): If your show has a lot of energy, use a slower attack (20ms+) to let some of the natural excitement through.

Final Tip: Trust Your Ears

At the end of the day, the best way to know if your compression sounds good is to listen. Does it sound natural? Are there any sudden volume changes? Does it feel like the audio is “breathing” too much? If something sounds off, tweak the settings and try again.

Compression might seem complicated at first, but once you get the hang of it, it’s one of the easiest ways to make your podcast sound more professional. Start with the example prompt, experiment with different settings, and soon you’ll have audio that sounds smooth and consistent—no audio engineering degree required.

Prompt 6: Mastering for Final Polish

You’ve spent hours recording, editing, and polishing your podcast. The voices sound clear, the pacing is tight, and the content is engaging. But there’s one last step that separates amateur audio from professional-quality sound: mastering.

Mastering is like the final coat of varnish on a piece of furniture. It doesn’t change the structure, but it makes everything look—and sound—better. It’s the process of balancing, enhancing, and optimizing your audio so it sounds consistent, polished, and ready for listeners. Without mastering, even the best-edited podcast can sound flat, uneven, or unprofessional.

What Is Mastering, and Why Does It Matter?

Mastering is the final step in audio production. It’s not the same as EQ or compression—those are tools used during editing to fix individual issues. Mastering takes the entire mix and makes it sound cohesive, loud enough (but not too loud), and ready for distribution.

Think of it like baking a cake. You mix the ingredients (recording), bake it (editing), and then add the frosting (mastering). The frosting doesn’t change the cake, but it makes it look and taste better. Mastering does the same for your podcast.

A well-mastered podcast has:

• Consistent volume (no sudden loud or quiet parts)
• Balanced frequencies (no muddy lows or harsh highs)
• Professional loudness (matches industry standards)
• Stereo width (sounds full and immersive)

Without mastering, your podcast might sound great on your headphones but weak on a phone speaker. Or it might clip (distort) when played on certain platforms. Mastering ensures your audio sounds good everywhere—from earbuds to smart speakers.

How to Write an AI Prompt for Mastering

AI tools can handle mastering for you, but you need to give them clear instructions. A good mastering prompt tells the AI:

1. The target loudness (usually -16 LUFS for podcasts)
2. The true peak limit (to prevent distortion)
3. Any final EQ adjustments (like a slight high-end boost)
4. Stereo widening (if you want a fuller sound)

Here’s an example prompt you can use: “Master the audio to -16 LUFS with a true peak of -1 dB. Apply a gentle EQ boost at 10kHz for clarity, and add subtle stereo widening. Keep the sound natural and avoid over-compression.”

This tells the AI exactly what you want without overcomplicating things. Some tools, like LANDR or Auphonic, let you adjust settings after the AI does its initial pass. That way, you can fine-tune the results to match your style.

AI Mastering Tools: Which One Should You Use?

Not all AI mastering tools are the same. Some are better for podcasts, while others are designed for music. Here’s a quick comparison:

• LANDR – Great for music, but can be too aggressive for spoken word. Best if you want a polished, radio-ready sound.
• Auphonic – Designed for podcasts. It handles loudness, EQ, and noise reduction well. Good for beginners.
• iZotope Ozone – More advanced, with manual controls. Best if you want to tweak settings yourself.

If you’re just starting, Auphonic is a safe choice. It’s simple, effective, and designed for podcasts. LANDR is better if you want a more musical sound, but you might need to adjust settings to avoid over-processing.

Before and After: The Difference Mastering Makes

Still not convinced? Listen to a podcast before and after mastering. The unmastered version might sound fine, but the mastered one will have:

• More clarity (voices sound crisper)
• Better balance (no sudden volume jumps)
• Fuller sound (less hollow or thin)

It’s like the difference between a home video and a Hollywood movie. Mastering doesn’t change the story, but it makes it more enjoyable to listen to.

Common Mastering Mistakes to Avoid

Even with AI tools, it’s easy to make mistakes. Here are a few to watch out for:

• Over-limiting – Too much compression can make your audio sound squashed and lifeless. Keep dynamics natural.
• Ignoring mono compatibility – Some listeners use smart speakers or phones with mono playback. If your stereo widening is too extreme, it might sound weird in mono.
• Too much EQ – A slight boost at 10kHz can add clarity, but too much makes voices sound harsh.
• Wrong loudness target – -16 LUFS is standard for podcasts. Going louder can cause distortion on some platforms.

Mastering is the final step, but it’s not the only step. If your recording is noisy or your editing is sloppy, mastering won’t fix it. But when done right, it takes your podcast from good to great.

Final Thoughts

Mastering might seem complicated, but with the right tools and prompts, it’s easier than you think. Start with a simple AI prompt, listen to the results, and adjust as needed. Your listeners will notice the difference—even if they don’t know why.

Try mastering your next episode and see how it sounds. You might be surprised at how much better it makes your podcast.

Putting It All Together: A Step-by-Step Workflow

You’ve got the prompts. You’ve tested the tools. Now it’s time to make your podcast sound professional—without spending hours in front of a screen. The secret? A simple, repeatable workflow that handles the heavy lifting for you. Let’s break it down step by step, so you can edit an episode in minutes, not days.

The Ideal Podcast Audio Workflow (Order Matters!)

Not all audio edits are created equal. Do things in the wrong order, and you’ll waste time fixing mistakes. Here’s the best way to process your podcast:

1. Noise reduction first – Clean up background hum, fan noise, or room echo before anything else. If you EQ or compress noisy audio, you’ll just make the noise louder.
2. EQ next – Cut harsh frequencies and boost clarity. This makes voices sound natural before compression squashes them.
3. Compression – Smooth out volume spikes so quiet parts aren’t too soft and loud parts don’t distort.
4. Normalization – Bring the whole episode to a consistent loudness (aim for -16 LUFS for podcasts).
5. Mastering last – Add the final polish (light EQ, stereo widening, and limiting) to make it sound “radio-ready.”

Why this order? Because each step builds on the last. If you normalize before noise reduction, you’ll amplify the noise. If you compress before EQ, you might boost frequencies you later want to cut. Stick to this sequence, and your audio will sound clean every time.

Batch Processing: Edit Multiple Episodes at Once

Editing one episode at a time is slow. Instead, process them in batches. Here’s how:

• Record multiple episodes in one session (if possible). Same mic, same room, same settings = consistent sound.
• Use AI tools to automate the first pass (noise reduction, EQ, compression). Descript, Auphonic, and Adobe Podcast can handle this in seconds.
• Review and tweak manually (if needed). AI isn’t perfect—listen for unnatural artifacts or over-compression.
• Export all episodes at once with the same settings (MP3, 128-192 kbps, -16 LUFS).

This way, you’re not starting from scratch every time. One setup, multiple episodes—done.

AI Tools for End-to-End Processing

You don’t need expensive software to sound great. Here’s a simple combo that works for most podcasters:

• Descript – Edit audio like a Word doc (cut silences, fix mistakes, add music). Its “Studio Sound” feature handles noise reduction and EQ automatically.
• Auphonic – Normalize levels, balance multiple speakers, and master the final file. Just upload, set your target LUFS, and let it run.
• Zapier (optional) – Automate the workflow. Example: When you upload a new episode to Dropbox, Zapier sends it to Auphonic for processing, then saves the final file to Google Drive.

This setup saves hours. No more manual tweaking—just upload, process, and publish.

Case Study: How One Podcast Saved 10+ Hours Per Month

Let’s look at a real example. The Daily Grind, a business podcast with 50+ episodes, used to spend 2-3 hours editing each episode. After switching to an AI-powered workflow:

• Time saved: 10+ hours per month (from 15 hours of editing to just 5).
• Listener feedback: “Your audio sounds so much clearer now!” (comments on Apple Podcasts).
• Retention rates: Increased by 15% (listeners stayed longer, likely because the audio was more consistent).

Their secret? They stopped doing everything manually. Instead, they:

1. Recorded in a quiet room (minimizing noise reduction work).
2. Used Descript to cut silences and fix mistakes in minutes.
3. Sent the file to Auphonic for normalization and mastering.
4. Published without second-guessing the audio quality.

The result? More time for content, less time for editing—and happier listeners.

Lessons Learned & Best Practices

After helping dozens of podcasters streamline their workflows, here’s what works best:

• Start with good recording habits. The better your raw audio, the less work AI has to do. Use a decent mic, record in a quiet room, and speak at a consistent distance from the mic.
• Don’t over-edit. AI tools are powerful, but they’re not magic. If your recording is too noisy or distorted, no tool can fix it perfectly.
• Test different LUFS levels. -16 LUFS is the podcast standard, but some platforms (like Spotify) prefer -14. Try both and see what sounds best to you.
• Listen on multiple devices. Your audio might sound great on headphones but muddy on phone speakers. Test before publishing.
• Automate what you can. If you’re doing the same steps every episode, find a way to automate them (Zapier, scripts, or presets in your DAW).

The goal isn’t perfection—it’s consistency. When every episode sounds the same, listeners trust your brand. And with AI tools handling the technical stuff, you can focus on what really matters: great content.

Advanced Tips and Pro Hacks

AI audio tools are powerful, but the real magic happens when you push them beyond basic settings. Think of AI like a smart assistant—it can do the heavy lifting, but you still need to guide it for the best results. Here’s how to take your podcast audio to the next level with advanced techniques.

Fine-Tuning AI for Niche Podcasts

Not all podcasts sound the same, and your AI prompts shouldn’t either. A music-heavy show needs different treatment than an ASMR podcast or a non-English interview. For example:

• ASMR recordings: Tell the AI to preserve subtle mouth sounds and gentle breaths. A prompt like “Remove only harsh background noise, keep natural ASMR textures” works better than a generic noise reduction command.
• Non-English podcasts: Some AI tools struggle with accents or languages they weren’t trained on. Specify the language (e.g., “Normalize levels for Spanish speech”) to avoid unnatural processing.
• Music-heavy shows: If your podcast includes songs or instrumentals, use prompts like “EQ voices without affecting music frequencies” to avoid muddying the mix.

The key? Always test different prompts on a short clip before processing the full episode.

Microphone-Specific Tweaks

Your microphone type changes how AI should process your audio. Dynamic mics (like the Shure SM7B) have a warmer, flatter sound, while condenser mics (like the Blue Yeti) pick up more detail—and more noise. Try these adjustments:

• For dynamic mics: Use lighter compression (e.g., “Apply gentle compression to even out levels without squashing dynamics”). These mics already reject background noise, so aggressive processing can make voices sound flat.
• For condenser mics: Prioritize noise reduction first (e.g., “Remove room echo and hiss before normalizing”). Then, use EQ to tame harsh highs or boomy lows.

Pro tip: If you switch mics often, save presets in your AI tool for each setup. This saves time and keeps your sound consistent.

When to Override AI (And How)

AI is smart, but it’s not perfect. Sometimes, it removes too much—like natural pauses that add emotion or dramatic effect. Here’s when to step in:

• Preserve intentional silence: If you use pauses for emphasis, add a note like “Keep natural pauses longer than 0.5 seconds” to the prompt.
• Manual EQ tweaks: AI might over-correct frequencies. For example, it could dull a bright voice by cutting too many highs. After the AI processes your audio, open it in a DAW (like Audacity or Adobe Audition) and make small adjustments.
• Compression limits: Some AI tools over-compress, making voices sound robotic. If this happens, dial back the settings or use a lighter preset.

Think of AI as a starting point, not the final product. A quick manual review can make a big difference.

The Future of AI Audio Engineering

AI is evolving fast, and new features are changing how podcasters work. Here’s what’s coming next:

• Real-time processing: Tools like Descript’s “Studio Sound” already clean up audio as you record. Soon, live podcasts could use AI to fix issues on the fly—no post-production needed.
• Voice cloning and restoration: Imagine reviving old interviews with poor audio or cloning your voice to fix mistakes without re-recording. Companies like ElevenLabs are making this possible.
• AI-driven mixing: Future tools might analyze your entire episode and suggest EQ, compression, and even music placement based on your content.

For now, experiment with these advanced techniques to stay ahead. The best podcasters combine AI efficiency with human creativity—so don’t be afraid to break the rules and find what works for your show.

Conclusion (~300 words)

Great podcast audio doesn’t happen by accident—it comes from small, smart tweaks. The six prompts we covered give you a simple way to fix common problems like background noise, uneven volume, and muffled voices. Let’s quickly recap what each one does:

• Silence removal – Cuts out awkward pauses so your episode flows better
• Volume normalization – Makes sure all voices sound equally loud
• EQ adjustments – Clears up muddy audio and makes voices crisp
• Noise reduction – Removes hums, fans, or street sounds without hurting your voice
• Compression – Smooths out loud and quiet parts for a professional sound
• Mastering – Adds the final polish so your podcast sounds like it was made in a studio

The best part? You don’t need to be an audio expert to use these. AI tools do the heavy lifting—you just need to guide them with the right prompts. Start with one or two tweaks, listen to the difference, and then try more. Even small changes can make your podcast sound 10x better.

Next Steps to Improve Your Audio

If you want to go deeper, here are some easy ways to learn more:

• Free tutorials: Check out YouTube channels like Podcastage or The Podcast Host for step-by-step guides
• AI tool demos: Many platforms (like Descript, Adobe Podcast, or Auphonic) offer free trials—test them out!
• Communities: Join Facebook groups or Reddit threads (like r/podcasting) to ask questions and share tips

Now it’s your turn. Pick one prompt from this list, run your latest episode through an AI tool, and listen to the difference. Did it work? What would you tweak next? Drop a comment below—we’d love to hear how it went! And if you found this helpful, subscribe for more podcasting tips and AI guides. Your listeners (and your future self) will thank you.