How to Clean Audio in Adobe Audition for Better Transcription Accuracy (Prep Checklist)

To get better transcription accuracy, you don’t need “perfect” audio—you need speech that is clear, even, and easy to follow. Adobe Audition can help you reduce steady noise, tame harsh “S” sounds, smooth volume swings, and remove hums and clicks so a transcriber (human or AI) makes fewer mistakes.

This prep checklist walks you through simple, repeatable steps: capture a noise print, roll off rumble, reduce sibilance, control peaks, and sanity-check the result before you export a clean WAV for transcription.

Primary keyword: clean audio in Adobe Audition for transcription

Key takeaways

• Start with fixes that remove obvious problems (hum, clicks, rumble) before heavy noise reduction.
• Use gentle settings and compare often; over-processing can make speech harder to transcribe.
• Aim for consistent speech level and controlled peaks, not “loud at all costs.”
• Evaluate with short before/after loops and headphones, then export a WAV for transcription.

Before you start: set up a safe, repeatable editing session

Make a copy of your original file and work on the duplicate so you can always go back if processing goes too far. In Audition, you can also save a new version name (for example, “Interview_CLEAN_v1”).

Pick a short section that represents the whole recording—about 10–20 seconds with both speech and background noise—and use it as your “test loop” for before/after comparisons.

Quick prep checklist

• Listen first: identify the biggest issue (hiss, hum, room tone, plosives, harsh S sounds, clicks).
• Use headphones: small artifacts hide on speakers.
• Watch the waveform: look for clipped tops (flat peaks) and sudden spikes.
• Fix the worst problems first: hum/click removal and rumble filtering usually help noise reduction work better.

Step 1: Remove hums, clicks, and obvious artifacts first

Steady hum (often from power or cables) and sharp clicks (from bumps, mouth noise, or digital glitches) can distract both people and transcription tools. If you reduce these early, later processing needs less force.

Hum removal (50/60 Hz and harmonics)

• What it sounds like: a low, steady buzz under everything.
• Good starting range: notch the base hum (50 Hz or 60 Hz) and, if needed, lightly reduce a few harmonics (100/120, 150/180, 200/240 Hz).
• Keep it gentle: heavy notches can thin out voices, especially deeper speakers.

If you’re not sure whether the hum is 50 or 60 Hz, try one and A/B it against the other. Use the setting that reduces buzz while keeping voices natural.

Click/pop repair

• What it sounds like: short ticks, crackles, or one-time pops.
• Good approach: target the specific click region when possible, then apply a conservative “click removal” pass.
• Recommended mindset: run two light passes instead of one aggressive pass to avoid dulling consonants.

For single, loud bumps, manual repair (zoom in, select the spike, and repair) often beats a blanket setting across the whole file.

Step 2: Use a high-pass filter to cut rumble and mic handling noise

A high-pass filter (HPF) removes low frequencies that are rarely useful for speech clarity but often contain rumble, HVAC vibration, wind, and desk bumps. This step alone can make voices sound cleaner and easier to understand.

Recommended high-pass filter ranges (speech-focused)

• Most spoken word (general): start around 70–100 Hz.
• Deeper voices or bassy mics: start around 60–80 Hz.
• Noisy field recordings: you may need 100–120 Hz, but stop if voices get thin.

Use a moderate slope and increase the cutoff slowly while listening to vowels; when the voice starts to lose “body,” back off a little.

Step 3: Noise reduction with a noise print (use less than you think)

Noise print reduction works best on steady background noise like hiss, fan noise, or consistent room tone. It can also hurt transcription accuracy if you push it too far, because aggressive reduction can create watery or robotic artifacts that smear consonants.

How to capture and apply a noise print (simple workflow)

• Find “silence”: select a moment with no speech—just background noise (1–3 seconds is often enough).
• Capture the noise print: store that noise profile.
• Apply reduction: process the full file using a conservative amount.
• Compare: A/B with your test loop; stop when the noise is lower but speech stays crisp.

Recommended setting ranges (keep it natural)

• Reduction amount: light-to-moderate reduction is usually safer than extreme reduction.
• Focus on consistency: reduce the noise floor a bit so speech stands out, rather than trying to eliminate all noise.
• Artifacts check: listen for swirly highs, “underwater” sound, or chirping around consonants.

If your recording has changing noise (coffee shop, moving car, shifting mic), noise print reduction may only help in short sections. In that case, process in chunks rather than the whole file at once.

Step 4: De-ess to tame harsh “S” sounds without dulling speech

Sibilance (“S,” “SH,” “CH”) can sound sharp and can confuse transcription when it masks nearby syllables. De-essing reduces that harsh band while keeping the rest of the voice intact.

Recommended de-essing ranges

• Target area (typical): often in the 4–10 kHz range.
• Start gentle: aim for small reductions on the strongest “S” peaks.
• Warning sign: if the voice starts to lisp or lose clarity, back off.

Use a loop with lots of “S” words and adjust until those peaks calm down but consonants still sound clear.

Step 5: Compression for more even volume (don’t crush it)

Transcription gets harder when speakers drift from whisper-quiet to suddenly loud. Light compression reduces those swings so words stay audible and peaks don’t jump out.

Recommended compression ranges for spoken word

• Ratio: about 2:1 to 4:1 for most dialogue.
• Attack/release: use moderate settings so you don’t blunt consonants or pump background noise.
• Gain reduction goal: aim for a few dB of reduction on loud phrases, not constant heavy reduction.

If compression brings up room noise too much, reduce the compression strength or revisit earlier steps (HPF, hum removal, noise reduction) with gentle adjustments.

Step 6: Normalize and/or limit to prevent clipping and set a sensible level

Normalization and limiting help you deliver audio that plays at a consistent, reasonable loudness without clipping. For transcription prep, you want clean headroom and clear speech, not maximum loudness.

Practical targets (safe starting points)

• Peak normalize: consider normalizing so peaks land around -3 dB to -1 dB.
• Limiter ceiling: set a ceiling around -1 dB to avoid accidental overs.
• If audio is already clipped: normalization won’t fix distortion; focus on reducing clipping at the source next time (mic gain, distance).

After limiting, re-check the loudest moments to confirm they sound clean and not squashed.

Before/after evaluation: quick tests that catch over-processing

Cleaning audio should make words easier to understand, not just make the background quieter. Use short, repeatable tests so you don’t “get used to” a processed sound that actually hurts clarity.

Evaluation checklist (2–3 minutes)

• A/B in a loop: toggle between original and cleaned on the same 10–20 seconds.
• Listen for consonants: T, K, P, S should stay crisp; if they smear, reduce processing.
• Check quiet words: make sure soft phrases are still intelligible without pushing noise too high.
• Try a “bad speaker” test: play it quietly on laptop speakers; you should still follow the words.
• Watch for artifacts: warbling, chirps, metallic highs, or pumping noise are signs to back off.

Common “too far” signs (and what to do)

• Underwater/robot voice: reduce noise reduction amount, or process in smaller sections.
• Thin, tinny dialogue: lower the high-pass cutoff and undo aggressive hum notches.
• Lisping: ease up on de-essing or narrow the target band.
• Breathing and room noise jump up: reduce compression or use less makeup gain.

Export settings and handoff workflow (transcription-ready)

Once the audio sounds clean and natural, export in a format that preserves quality and avoids extra compression artifacts. WAV is a common choice for transcription prep because it is uncompressed and widely supported.

Recommended export basics

• Format: WAV
• Sample rate/bit depth: if you’re not sure, keep the original project settings; avoid upsampling just to “make it better.”
• Channels: keep mono or stereo as recorded; don’t downmix if it makes speakers harder to separate.
• File naming: include date and speaker or episode number (example: “Podcast_E12_CLEAN.wav”).

Suggested end-to-end workflow

• 1) Clean the audio in Audition: hum/click repair → high-pass filter → noise print reduction → de-ess → light compression → normalize/limit.
• 2) Export a clean WAV: save a “clean” version separate from your original.
• 3) Choose your transcription path: upload the cleaned audio for human transcription, or use automated transcription and then request a cleanup pass if needed.
• 4) Reduce edits: cleaner audio usually means fewer misheard words and less time fixing names, numbers, and jargon.

If you want to compare options, you can start with automated transcription for speed and then move to a human-reviewed version when accuracy matters more.

If you already have a draft transcript (from any tool), consider transcription proofreading services to polish wording, speaker labels, and difficult passages—especially for noisy interviews.

Common questions

• Should I always do noise reduction before EQ?
  Usually no; remove obvious hum/clicks and apply a high-pass filter first, then use noise reduction gently.
• How much noise reduction is “safe” for transcription?
  Enough to lower steady hiss or fan noise while keeping consonants crisp; if you hear warbling or metallic highs, you’ve likely gone too far.
• Will compression make transcription easier?
  Light compression can help by keeping soft words audible and controlling peaks, but heavy compression can raise room noise and hurt clarity.
• Do I need to normalize if I used compression?
  Often yes; compression changes dynamics but doesn’t guarantee sensible peaks, so a final normalize/limiter step helps prevent clipping.
• Is WAV required for transcription?
  Not always, but WAV avoids extra compression artifacts and is a safe choice when you want the cleanest handoff.
• What if my audio is clipped or distorted?
  Cleanup can only do so much; try gentle repair, but plan to fix the recording chain next time (lower input gain, better mic placement).

When you finish your cleanup pass, GoTranscript can help you turn that improved audio into a reliable transcript with fewer back-and-forth edits. You can upload your file and choose the right level of support through our professional transcription services.