What is Auphonic?
Auphonic is an AI-powered audio editor that automates audio post production for podcasts, videos, audiobooks, educational recordings, and broadcast content. It applies a suite of AI algorithms to uploaded audio or video files — handling noise reduction, level balancing, frequency correction, filler word removal, loudness normalization, speech-to-text, and multitrack mixing — without requiring manual editing knowledge. The tool is browser-based with API and CLI access, and is free for up to 2 hours of audio per month.
Features & Benefits
- Noise & reverb reduction – Remove static or fast-changing background noise, reverb, and breath sounds using AI classifiers that distinguish speech from music and ambient audio. Control noise, reverb, and breath reduction levels independently.
- Intelligent Leveler – Balance loudness between speakers and between music and speech using adaptive dynamic range compression trained on real audio data, without manual compressor adjustments.
- AutoEQ & Bandwidth Extension – Automatically correct the frequency spectrum per speaker, removing sibilance and plosives with time-dependent EQ profiles. Recover high frequencies lost in archival or low-bitrate recordings via Bandwidth Extension.
- Filler word & silence removal – Detect and cut silent segments, pauses, coughs, and filler words such as “ah” and “uhm” across multiple languages. Review and edit cuts manually in the Audio Inspector or export cut lists for external editors.
- Multitrack processing – Process separate audio tracks from multiple microphones, music sources, and remote speakers into a balanced mixdown with automatic ducking, adaptive noise gates, and mic bleed removal per track.
- Loudness normalization – Define target loudness parameters including integrated loudness, true peak, MaxLRA, and dialog normalization for compliance with podcast, broadcast, and platform specs including ACX/Audible, EBU R128, and ATSC A/85.
- Speech-to-text & shownotes – Transcribe audio using a self-hosted OpenAI Whisper model with per-speaker timestamps, auto-generated chapter markers, and AI-summarized shownotes in a shareable transcript editor.
- Video support & audiograms – Extract, process, and re-merge audio from video files without image quality loss. Generate waveform audiogram videos from audio-only productions for social sharing.
- Watch folders & batch processing – Automatically trigger processing when files are added to connected cloud storage. Batch process multiple files using presets. Available on paid plans.
- Publishing integrations – Publish processed audio and video directly to YouTube, Libsyn, Blubrry, Spreaker, PodBean, Podlove, Soundcloud, RSS.com, Acast, Scrybecast, and Facebook.
- File transfer integrations – Move files automatically between Auphonic and Dropbox, Google Drive, OneDrive, Amazon S3, SFTP, and FTP servers.
Real-World Applications
Podcast producers recording multi-guest episodes can use Auphonic as their primary audio editor to handle the full post production chain without a DAW. Uploading separate tracks per speaker lets the multitrack algorithm balance loudness, remove mic bleed, and apply noise reduction before producing a finished mixdown. Automatic filler word and silence removal cuts editing time on long-form interviews significantly — processing typically completes in about 5% of the audio’s duration.
Audiobook narrators producing for Audible/ACX can use the RMS-based loudness normalization to meet submission specs in one step. AutoEQ and Bandwidth Extension correct frequency issues in recordings made in untreated rooms, reducing the need for manual EQ work before submission. Output can be exported in the correct format and bit depth for direct ACX delivery without additional processing.
Educational institutions recording lectures can connect Auphonic to a watch folder on Google Drive or Dropbox so that recordings are automatically processed and published after upload, with no manual intervention. The Whisper-based speech-to-text produces accessible transcripts with per-speaker timestamps, supporting accessibility requirements for students and staff. This workflow scales across large volumes of recordings without adding production overhead.
Video creators producing remote interviews for YouTube can use Auphonic to process audio tracks and publish the finished video directly to YouTube from within the audio editor interface. The audiogram feature generates a waveform video from audio-only recordings for use on social platforms, removing the need for separate video editing software to produce a shareable visual asset.
