AI Tools to Separate Voices in Audio

Here’s a quick look at the most common problems podcasters face and how disruptive they are to the listening experience:

Background noise
Very High
92%
Plosive pops (P/B sounds)
High
78%
Room echo / reverb
High
85%
Clipping / distortion
Moderate
70%
Sibilance (harsh “S” sounds)
Moderate
60%
Mouth clicks / lip smacks
Moderate
55%

Listener distraction levels by audio problem type (estimated based on podcasting community surveys)

Why These Problems Happen

Most of these issues come from recording in untreated rooms, using budget microphones, or sitting too close to your mic. The great news is that all of them are fixable in post-production. That’s where learning how to clean speech for podcast editing saves the day.


Best Tools to Clean Speech for Podcast Editing

You don’t need to spend a fortune on software. In fact, some of the best speech-cleaning tools are completely free. Here’s an honest comparison:

Tool Price Best For Skill Level Noise Reduction
Audacity Free Beginners, full editing Beginner–Mid Good
Adobe Audition $54/mo (Creative Cloud) Professional podcasters Intermediate–Pro Excellent
iZotope RX $99–$399 Heavy repair work Intermediate–Pro Best in class
Descript Free–$24/mo Quick, AI-powered editing Beginner Very Good
VocalRemoverX Free online tool Voice isolation & separation Beginner Very Good
Reaper $60 (one-time) Full DAW editing, budget pick Intermediate Good (with plugins)
GarageBand Free (Mac only) Apple users, simple editing Beginner Decent

Comparison of popular podcast audio editing and speech-cleaning tools

For most beginners, Audacity is the best starting point. For those who need AI-assisted voice isolation quickly, VocalRemoverX is a fantastic free browser-based option that doesn’t require any downloads.

Pro Tip: Start with a free tool to learn the basics. Once you understand what each setting does, upgrading to a paid tool makes a real difference.

Step-by-Step: How to Clean Speech for Podcast Editing

This is the core of the guide. Follow these steps in order, and you’ll get professional-sounding audio every time.

Step 1 — Import and Organize Your Raw Audio

Open your editing software and import your raw recordings. Label each track clearly — host, guest 1, guest 2, music, and so on. Working organized saves a lot of time later.

Step 2 — Listen Through Once Before Touching Anything

Play through the full recording first. Take notes on where the biggest problems are. This gives you a roadmap before you start making changes.

Step 3 — Cut the Dead Air and Obvious Mistakes

Remove long pauses, false starts, and obvious stumbles. This makes the recording feel tighter before you even start on audio quality. Most editors delete anything over 1.5 seconds of silence.

Step 4 — Apply Noise Reduction

This is where you actively clean speech for podcast editing. Noise reduction removes the steady background hum — like fans, air conditioners, and computer noise. Here’s how to do it in Audacity:

  1. Find a section of your recording with only background noise (no talking). Even 1–2 seconds works.
  2. Select that section and go to Effect → Noise Reduction → Get Noise Profile.
  3. Select your entire audio track (Ctrl+A / Cmd+A).
  4. Go back to Effect → Noise Reduction and click OK. Start with Noise Reduction at 12 dB.
  5. Listen back. If the audio sounds “watery” or robotic, reduce the setting.

Step 5 — Remove Plosives and Mouth Sounds

Plosive pops are those harsh bursts when someone says “P” or “B” sounds too close to a mic. To fix them:

  • Use a high-pass filter set to around 80–100 Hz to cut low-frequency booms.
  • Zoom in on the waveform and manually reduce the peak of any plosive hit.
  • iZotope RX has a dedicated “De-click” and “De-plosive” tool that handles this automatically.

Step 6 — Use Equalization (EQ) to Shape the Voice

EQ is one of the most powerful ways to clean up speech. Here’s a simple starting point for voice EQ:

Frequency Range What It Controls Suggested Adjustment
Below 80 Hz Rumble, mic handling noise Cut with high-pass filter
200–300 Hz Muddiness, boxy sound Slight cut (–2 to –4 dB)
1,000–3,000 Hz Voice clarity and presence Slight boost (+2 to +3 dB)
4,000–6,000 Hz Consonant clarity, bite Boost slightly for brightness
8,000–12,000 Hz Air, sibilance Gentle boost or use de-esser
Above 12,000 Hz Hiss, high-frequency noise Low-pass filter or gentle cut

Basic EQ guide for podcast voice processing

Step 7 — Apply Compression

Compression evens out the volume differences in speech. When someone talks quietly, then suddenly gets loud, compression brings those levels closer together. For podcasts, a ratio of 3:1 or 4:1 with a medium attack and release works well for most voices.

Step 8 — De-ess the Harsh “S” Sounds

A de-esser is a plugin that targets harsh, hissy “S” and “SH” sounds. Set it to target the 5,000–8,000 Hz range. Apply gently — over-de-essing makes voices sound lispy and unnatural.

Step 9 — Normalize and Set Final Loudness

Most podcast platforms recommend a loudness of –16 LUFS (stereo) or –19 LUFS (mono). Use a loudness meter plugin or your software’s built-in normalization tool to hit these targets consistently.

–16

LUFS target (stereo)
–19

LUFS target (mono)
–1 dB

True peak maximum
3:1

Compression ratio for voice

Noise Reduction Techniques That Actually Work

Not all noise reduction is equal. There are several different approaches, and knowing which one to use in which situation makes a huge difference when you clean speech for podcast editing.

Spectral Editing — The Surgeon’s Approach

Spectral editing lets you see your audio as a visual map of frequencies over time. You can literally paint away noise. iZotope RX is the gold standard here. It’s like Photoshop for audio — you can spot a dog bark or a siren and erase it without affecting the speech around it.

Gate vs. Expander — Know the Difference

A noise gate completely silences audio that falls below a set volume threshold. An expander does the same thing but more gradually. For podcasting, expanders are usually better because they don’t create abrupt, unnatural silences.

Technique How It Works Best Used For Risk
Noise Gate Cuts audio below a threshold Rooms with intermittent noise Choppy sound if set too high
Noise Expander Gradually reduces quiet sounds General background noise reduction Low — very natural sounding
Spectral Repair Removes specific frequency events One-off sounds (sirens, coughs) Time-consuming on long files
AI Noise Removal Machine learning identifies speech vs. noise Fast, broad noise cleanup Can sound “processed” if overused

Comparison of noise reduction techniques for podcast speech cleaning

AI-Powered Noise Removal — The Fast Lane

AI tools like Adobe Enhance Speech (free), NVIDIA RTX Voice, and online tools such as VocalRemoverX use machine learning to separate speech from background noise automatically. They work remarkably well on most recordings, making them a great choice when you need to clean speech for podcast editing quickly.


Advanced Speech Cleaning Tips for Better Results

Once you’ve mastered the basics, these next-level techniques will take your podcast audio to another level.

Record in a Treated Space First

The single best way to clean speech for podcast editing is to not need much cleaning at all. Record in a space with soft surfaces — a bedroom with carpet, a walk-in closet, or a small room with acoustic foam panels. Hard walls create echo; soft materials absorb it.

Use Multiband Compression for Uneven Voices

Regular compression treats all frequencies the same. Multiband compression lets you compress different frequency ranges independently. This is especially helpful when a guest’s voice is bassy and boomy in some moments and thin in others.

Match Loudness Across Multiple Guests

When you have multiple speakers recorded on separate tracks, their levels almost never match. Use a gain plugin or trim each track manually before applying compression. The goal is to make all voices sound like they’re in the same room at the same distance from the mic.

Watch out: Over-processing audio is a real danger. If your voice sounds like it’s coming through a phone or has a “watery” quality, you’ve pushed the noise reduction too hard. Less is almost always more.

Use a Limiter at the End of Your Chain

After all your processing, place a limiter as the very last plugin. Set the ceiling at –1 dB true peak. This prevents any accidental clipping from sneaking into your final export.

Create a Standard Processing Chain (Template)

Once you find a workflow that sounds great, save it as a template in your DAW. That way, every episode starts with the same processing applied automatically. This saves time and keeps your show sounding consistent from episode to episode.


Mistakes to Avoid When Cleaning Podcast Audio

Even experienced editors fall into these traps. Here’s what to watch out for when you clean speech for podcast editing:

Mistake What Happens How to Fix It
Too much noise reduction Voice sounds robotic or “watery” Use a lower dB setting; reduce smoothing
Skipping EQ Voice sounds muddy or too thin Apply a basic 3-band EQ to every track
Ignoring LUFS targets Show sounds too loud or too quiet on platforms Use a loudness meter and normalize to –16 LUFS
Not checking on headphones Issues missed that listeners will hear Always do a final pass on earbuds or headphones
Editing on a bad monitoring environment False sense of quality in a reverberant room Use closed-back headphones for editing
Compressing before noise reduction Noise gets amplified during compression Always do noise reduction first, then compress
Exporting in the wrong format File too large or quality too low Export as MP3 at 128–192 kbps for most podcasts

Common podcast audio editing mistakes and how to correct them

Quick Rule: Always process audio in this order — noise reduction → EQ → compression → de-essing → limiting. Doing it out of order causes each plugin to work against the others.

Frequently Asked Questions

Q: What does it mean to clean speech for podcast editing?
It means removing unwanted sounds from a voice recording — things like background noise, room echo, plosive pops, mouth clicks, and hiss — so the speech sounds clear and professional to listeners.
Q: Can I clean podcast audio for free?
Yes. Tools like Audacity, GarageBand (Mac), and browser-based tools like VocalRemoverX let you clean speech without spending a dime. Paid tools like iZotope RX offer more power, but free tools handle most problems well.
Q: How do I remove background noise from a podcast recording?
The most common method is noise reduction using a “noise profile.” You select a section of background-only noise, let the software analyze it, and then apply noise reduction to the whole track. Audacity makes this easy with its built-in Noise Reduction effect.
Q: What loudness should a podcast be?
Most podcast platforms, including Spotify and Apple Podcasts, recommend a loudness of –16 LUFS for stereo recordings and –19 LUFS for mono. Your true peak should not exceed –1 dBTP.
Q: Should I use a noise gate or noise reduction?
Both have their place. Noise reduction removes steady background noise (like fan hum or room tone) that’s present throughout the recording. A noise gate silences the mic between words during pauses. For most podcasters, noise reduction should come first, and a gate (or expander) is added on top if needed.
Q: How long does it take to edit and clean one hour of podcast audio?
For a beginner, it can take 3–5 hours per hour of recording. As you get faster and build templates, this drops to 1–2 hours. Using AI tools can cut that down even further, sometimes to under 30 minutes for a clean recording.
Q: What file format should I export my podcast in?
For most podcasts, MP3 at 128 kbps (mono) or 192 kbps (stereo) is the standard. It keeps file sizes manageable while maintaining good audio quality. WAV or AIFF is better for archiving but too large for distribution.
Q: Is AI audio cleaning good enough for professional podcast production?
AI tools have improved massively in recent years. For most podcasts, AI-based noise removal (like Adobe Enhance Speech or VocalRemoverX) produces results that are more than good enough for professional release. For very damaged recordings, combining AI cleanup with manual spectral editing gives the best results.