Every editor who works with long recordings has experienced the same problem: you open an NLE with a four-hour file and a blank timeline, and the first task is not cutting — it is figuring out what is in the recording. Where are the highlights? Where are the problems? What is the structure?
Automatic audio markers solve this problem by analyzing the recording before the editing session begins. Instead of starting with a blank timeline, editors start with a timeline that already shows the structure — highlights, risks, chapter breaks, cutter instructions — all placed at the exact timestamps where they occur.
This article explains how automatic audio markers work, what kinds of detections they make, and how they integrate with the editing tools editors already use. For stream editors handling long VODs, see how stream editors save time with CutCue.
Key Takeaways
- Automatic audio markers analyze a recording before the editing session begins, replacing the manual discovery phase with a pre-annotated timeline.
- CutCue detects highlights, chapters, demonetization risks, cutter instructions, chat activity peaks, Twitch events, and alert sounds — all from the audio track.
- A 6.5-hour stream processes in under 15 minutes; a one-hour recording in 2–3 minutes.
- Markers export to Premiere Pro (CSV — requires the free “CSV Marker Importer” plugin from Adobe Exchange), DaVinci Resolve (XML), and Vegas Pro (C Script).
What Are Automatic Audio Markers?
An audio marker in the context of video editing is a flag placed at a specific timestamp in a timeline. Editors use them manually all the time — to mark a good take, note a problem, identify a chapter break, or flag a moment for review.
Automatic audio markers are the same thing, but placed by automated analysis rather than by the editor manually. The analysis processes the audio track of a recording, applies several different detection models to the content, and generates a set of markers that correspond to specific findings — each one placed at the exact timestamp where the detection occurred.
The resulting marker file is exported in a standard format and imported into the editing project. From the editor’s perspective, it looks like a set of colored markers in the timeline, each labeled with the type of detection.
What Automatic Audio Markers Detect
Different types of analysis produce different categories of markers. CutCue generates markers across several detection categories:
Highlight and intensity markers. The analysis identifies moments in the audio where intensity is significantly elevated — reactions, emotional peaks, conversational climaxes. These are marked as potential highlights. They are suggestions, not guarantees — the editor’s judgment about whether a moment is worth using remains essential.
Clip and hook markers. Beyond general intensity, the analysis tags emotionally specific moments — funny exchanges, shocking statements, emotional passages — that are candidates for short-form clips, YouTube Shorts, or social media content. These are labeled by type so editors can quickly locate the category of moment they are looking for.
Chapter markers. The analysis identifies significant topic transitions in speech and places chapter markers at the natural break points. This gives the editor an immediate overview of the recording’s structure without scrubbing through it.
Demonetization risk markers. Spoken words and phrases that match known ad-restricted terms on YouTube are flagged with timestamps and risk labels. This allows editors to address these moments before upload rather than discovering revenue loss after publishing.
→ See how CutCue’s demonetization checker works
Custom keyword markers. Any word or phrase defined by the user — brand names, sponsor references, competitor mentions, cutter instruction phrases, or project-specific terms — is detected and marked throughout the recording. Each occurrence is timestamped and labeled with the keyword that triggered it.
Chat Peak Analytics markers. For Twitch stream recordings, CutCue detects spikes in chat activity — moments when viewer engagement in chat was at its peak. These peaks appear as markers in the timeline and provide an audience-based signal that complements the audio-intensity-based highlight detection. The overlap between a chat peak and an audio highlight is typically the strongest indicator of a clip-worthy moment.
Stream event markers. CutCue identifies specific Twitch events — subscriber notifications, resubs, gift subs, bits donations, and raid alerts — and marks each with a precise timestamp. For stream editors building subscription compilations or donation highlight reels, these markers replace manual event tracking entirely. Stream event detection is included from the Creator plan upward.
Stream alert markers. For stream recordings, editors can upload audio samples of the donation sound, subscriber alert, or other notification sounds used by the streamer. CutCue matches these sounds throughout the full recording and places a marker at each occurrence. This is available in the Studio plan and works with any distinct audio sample.
How Markers Are Generated
The process from audio file to imported markers involves four steps:
Step 1 — Export audio. The audio track is exported from the video project or recording software. All standard audio formats are supported — MP3, WAV, AAC, M4A, FLAC, and others.
Step 2 — Upload and configure. The audio file is uploaded to CutCue. If custom keywords or stream alert samples are relevant to this project, they are set up at this point. No technical configuration is required beyond defining the terms and uploading samples.
Step 3 — Analysis runs in the background. CutCue processes the file. A 6.5-hour stream typically completes in under 15 minutes. A one-hour recording finishes in 2–3 minutes. The editor can work on other tasks while the analysis runs.
Step 4 — Import markers. The analysis produces a marker file in CSV format (for Premiere Pro), XML format (for DaVinci Resolve), or C Script format (for Vegas Pro). This file is imported into the editing project. Markers appear in the timeline at their exact timestamps, labeled by type and color-coded for quick navigation.
What the Timeline Looks Like After Import
Once the marker file is imported, the editor’s timeline contains a map of the entire recording. This is the core advantage: instead of navigating an unknown recording sequentially, the editor navigates by marker type.
Looking for highlights to build a clip compilation? Filter to highlight markers and jump between them. Reviewing the demonetization flags before upload? Navigate to each risk marker and make a decision. Building chapter structure? The chapter markers are already placed — review them, adjust if needed, and export. Checking for Twitch events or chat peaks? Jump directly to each timestamp without scrubbing.
The editor still makes every creative decision. The markers do not make the edit; they make the edit significantly faster by removing the discovery phase from the process.
Language coverage
Transcription, keyword detection, and transcript or caption-oriented outputs depend on what is enabled for your account, plan, and source language. See Help for current availability. Custom keywords apply within the same constraints.
Automatic audio markers remain useful when your workflow benefits from structured review signals — including teams that publish in more than one language, where coverage can vary by production.
Getting Started
CutCue plans start at €29 per month. Every plan includes transcription and chapter detection where supported for your workflow, transcript or caption-oriented outputs where supported, and the demonetization check where applicable. Highlight detection, chat peak analytics, stream event detection, and custom keywords are available from the Creator plan (€79/month) upward. Alert sound fingerprinting and priority processing are available in the Studio plan (€189/month).
Each analysis also produces a downloadable PDF report summarizing detected highlights, chapters, demonetization flags, and chat peaks — useful as a personal reference or a client-facing deliverable.
Markers are compatible with Adobe Premiere Pro, DaVinci Resolve, and Vegas Pro.
Frequently Asked Questions
In which formats does CutCue export markers?
CutCue exports markers in CSV format for Adobe Premiere Pro, XML format for DaVinci Resolve, and C Script format for Vegas Pro. DaVinci Resolve and Vegas Pro support native import. Premiere Pro requires the free “CSV Marker Importer” plugin, available on Adobe Exchange.
Can I define my own custom trigger phrases?
Yes. CutCue’s custom highlighters let you define any word or phrase as a keyword — cutter instruction phrases like “editor, cut this,” brand names, competitor references, or any project-specific term. Every occurrence is detected and timestamped in the resulting marker file.
How does alert sound fingerprinting work?
You upload a short audio sample (typically 5–15 seconds) of the sound you want to find — a donation alert, a subscriber notification, or any recurring audio cue. CutCue analyzes the full recording and places a marker at every point where that audio pattern appears. Alert sound fingerprinting is available in the Studio plan.
What is the difference between highlight markers and chapter markers?
Highlight markers identify specific moments of elevated intensity or emotional content — individual clips worth extracting. Chapter markers identify topic transitions — structural breakpoints that define the shape of the full recording. Both appear in the same timeline; editors use highlight markers to find content and chapter markers to understand structure.
