What is Auphonic?
Auphonic is an automatic audio post production service that applies AI audio processing to clean up and master recordings. Raw audio files almost always need work before they’re ready to publish. Noise, uneven levels, and filler words are standard problems that normally take time and technical skill to fix. Auphonic runs that entire process automatically and outputs broadcast-ready files.
It covers everything from noise removal and multitrack mixing to transcription and direct publishing. Podcasters, broadcasters, audiobook narrators, educators, and video creators all use it. No audio engineering background is needed to get professional-sounding audio post production results.
Auphonic Video
Features & Benefits
- Noise & Reverb Reduction: remove static or fast-changing background noise, room reverb, breaths, and mouth noises using AI denoising; adjust noise, reverb, and breath reduction levels independently, with control over whether music segments are kept or removed
- Intelligent Leveler: balance loudness between multiple speakers, music, and speech with adaptive dynamic range compression; no compressor knowledge required
- AutoEQ Filtering: apply per-speaker, time-dependent EQ profiles that cut sibilance and plosives automatically for a clear, consistent sound across voices
- Studio Voice Enhancement: reconstruct studio-quality speech from poor recordings; repairs clipping, codec artifacts, distortion, and damage from other voice processors
- Bandwidth Extension: restore missing high frequencies in archival or low-bitrate recordings to make speech sound brighter and more natural
- Automatic Cutting: detect and remove silent gaps, coughs, throat-clearings, sneezes, and filler words like “uh” and “um” in multiple languages; review and edit cuts manually in the Audio Inspector or export cut lists
- Multitrack Processing: combine multiple input tracks into an optimized mixdown with automatic ducking, per-track denoising, adaptive noise gates, and mic bleed removal
- Loudness Normalization: set target integrated loudness, true peak, MaxLRA, and dialog normalization to meet audio post production specs for podcast platforms, audiobook distributors, and broadcast standards including EBU R128 and ATSC A/85
- Speech-to-Text & Shownotes: transcribe audio using a self-hosted multilingual Whisper model or external services; auto-generate timestamped chapters and multi-level shownotes in a shareable transcript editor
- Video Processing: extract the audio track from video files, apply all processing, and merge it back without any loss of image quality
- Audiogram Generator: convert audio-only files into shareable waveform videos using cover art or chapter images as backgrounds
- Burn-In Subtitles: render timed captions directly into video or audiogram files with custom fonts, colors, and per-word karaoke-style highlighting
- Chapters & Metadata: add chapter marks and map metadata tags across multiple output files simultaneously
- Automatic Publishing: publish finished files directly to podcast hosts, video platforms, and audio distribution services
- Workflow Automation: connect to your pipeline via watch folders, a REST API, CLI, or Zapier; white label API available for custom integrations
What can Auphonic do?
- Remove background noise from podcast recordings
- Balance audio levels between multiple speakers
- Cut filler words and silence automatically
- Transcribe audio to text in multiple languages
- Generate podcast shownotes and chapters
- Normalize audio loudness for podcast platforms
- Mix and process multitrack audio recordings
- Remove room reverb from voice recordings
- Restore low-quality or archival audio recordings
- Add burned-in subtitles to video files
- Create waveform audiogram videos from audio files
- Publish audio to podcast hosting platforms
- Process audio extracted from video files
Real-World Applications
Getting a podcast episode from raw recording to publish-ready normally takes real editing time. Auphonic can handle the noise cleanup, level balancing, and filler word removal automatically, which cuts that process down to a file upload for independent podcasters recording at home.
Audiobook narrators face strict loudness requirements from distributors like Audible. Missing ACX targets means rejected files and resubmission. The RMS-based normalization and true peak limiting hit those specs automatically, and batch processing makes it practical across long projects.
Broadcast and media organizations processing content at scale use the API and watch folder support to run audio post production without manual intervention. Multitrack support covers segments recorded with remote guests across mismatched setups, and output loudness can be locked to EBU R128 or ATSC A/85 automatically.
Short-form video posted to social media often autoplays muted. Running a video file through Auphonic cleans the audio track and burns styled captions directly into the file in the same pass, with no separate captioning step needed.
Universities and e-learning teams may find that even basic noise reduction and leveling make lecture recordings noticeably easier to follow. Speech-to-text transcripts come out of the same production, which helps institutions meet accessibility requirements without extra tooling.
