Video sentiment analysis, line by line. The emotion in every passage, ready to filter.
Video sentiment analysis means reading what each line of a recording conveys, beyond the words. We read every passage of the transcript and tag its emotion and intensity, from gratitude and hope to tension and humor, with a timestamp. Filter by emotion, sort by the most intense lines and find the moment that moves people in minutes.
Updated
Sentiment analysis beyond positive and negative.
A positive-or-negative meter doesn't help an editor. Knowing that minute 32 is gratitude and minute 47 is tension does. So every passage gets named emotions, like love, hope, reverence, curiosity or sadness, plus an intensity from subtle to very strong. The vocabulary follows the kind of content: a sermon brings out faith, reverence and hope; a wedding, love, family and gratitude; a podcast, curiosity, humor and teaching. One passage can carry more than one emotion, the way real people actually talk. And because every tag sits on a timestamped line, one click takes you from the label to the exact moment in the player.
- Named emotions, not just positive and negative
- Intensity on every passage, so the peaks stand out
- Vocabulary tuned for sermons, weddings, podcasts, classes and more
- Works with audio and video
| Time | Line | Emotion | Intensity |
|---|---|---|---|
| 00:12:40 | “I showed up here with nothing, and God gave me a family.” | Gratitude, family | Very strong |
| 00:27:05 | “Maybe you're walking through the wilderness right now.” | Compassion | Medium |
| 00:33:18 | “Nobody thought that girl was going to graduate.” | Resilience | Strong |
| 00:47:52 | “What if next Sunday was your last one here?” | Tension | Strong |
Every line of gratitude, in one list.
In the Emotions tab, each emotion becomes a filter with its line count. Pick gratitude and see only those passages. Raise the intensity to keep only the strongest. Sort by most intense, by order in the video or by longest. Each line shows who spoke, when, and which other emotions it carries. Favorite what you need and download the passage as a file without opening your editor. In the transcript, the same emotion filter works alongside the speaker and chapter filters, so you can read, say, only the bride's most emotional lines during the ceremony.
- Filter by emotion, with a line count
- Intensity: any, strong or only the strongest
- Sort: most intense, video order or longest
- Favorite and download a passage right from the list
What is emotion analysis good for in editing?
A tagged emotion is an editing shortcut. A wedding filmmaker pulls the love and gratitude lines for the highlight film without replaying the whole reception. A church media team lifts the strongest lines of Sunday's sermon for the week's clips. A podcaster finds the spot where the conversation got tense, which often makes a great clip. With video, create a clip straight from an emotion and fine-tune its start and end word by word. On Studio and Agency, emotions also show up on hooks and on the scenes of your script.
- Manual clip from an emotion, for video
- Emotions on hooks and scripts, on Studio and Agency
- MP3 passages for audio, no editor needed
- Wedding: love, very strong, 6 lines for the highlight film
- Sermon: hope, strong, 4 passages for this week's clips
- Podcast: tension, 3 passages that could open the episode
- Testimonial: gratitude, 2 lines for the company video
How FilmScribe analyzes the emotions in a video or audio file
- 01
Upload the video or audio
An audio or video file, or a YouTube link. When you upload, pick the content type, like sermon, wedding or podcast, so the analysis uses the right vocabulary.
- 02
We tag the emotions
We transcribe, separate the speakers and tag the emotion and intensity of every passage. It all arrives together, with no extra step.
- 03
Filter and use it
Filter by emotion and intensity, favorite the lines you want and move them forward: a downloaded passage, a clip, a hook or a script.
Emotion analysis specs
- Where it shows
- The Emotions tab and every line of the transcript
- Per passage
- One or more named emotions, plus intensity
- Filters
- Emotion and intensity, plus speaker, chapter and favorites in the transcript
- Sorting
- Most intense, video order or longest
- Actions
- Favorite, download the passage and create a clip (video)
- Input
- Audio or video, in any language we transcribe
- Plans
- Every plan
More than emotions. Every line becomes an editing choice.
See also
Emotions are on every plan.
Compare plans →- Transcription with speakers and chapters
- Emotions in every line
- Automatic clips with animated captions
- Remove pauses and filler words
- Downloads without watermark
See all features
- Manual clips, trimmed word by word
- Saved clip templates for the next ones
- Emotion filter
- Favorite and export lines in bulk
- Export as TXT, PDF, SRT, MP3 and MP4
- Everything in Pro
- Scored hooks and scripts
- Timeline for Premiere, DaVinci and Final Cut
- Translation and speaker names
- Your logo and your font on clips
- Connector for ChatGPT, Claude and Gemini
- Team: each person at R$ 29/month, with 3 more hours
See all features
- Moments inside each chapter
- Diagrams: mind map, flow and timeline
- Image and font library for clips
- Projects to organize by client
- Support
- Everything in Studio
- FilmScribe Plugin for DaVinci Resolve Studio (beta)
- Team with 2 people included
- Priority support
- Extra hours at R$ 7
3-day trial or 1 hour of material. See the result on your own recording before adding a card.
Frequently asked questions
How can I analyze emotions in a video?
Upload the file or paste a YouTube link. We transcribe it, separate the speakers and tag the emotion and intensity of every passage. You get a list you can filter by emotion and sort by the most intense lines. The same upload also gives you chapters and, on Studio and Agency, hooks, a script and diagrams.
What is video sentiment analysis?
It's reading what each passage of a video conveys: joy, tension, hope or sadness, and how strongly. Basic sentiment analysis only splits positive from negative. Here every passage gets named emotions and an intensity from subtle to very strong, using the vocabulary of your content type, like a sermon, a wedding or a podcast.
Which moments carry the most emotion?
Sort the lines by intensity and the strongest rise to the top, each with its exact timestamp. Filter by a single emotion, like gratitude or hope, and keep only its strongest lines. Click a line to hear the passage and confirm it before you use it. It's the shortest path to the line that deserves to open a video.
How is emotion detected in speech?
We read what was said in each passage, in the context of the conversation and the content type you chose, and tag the emotions present and how strong they are. The reading starts from the words, so it's worth listening before you publish: sarcasm and tone of voice sometimes need your ear.
Can it help me pick clips?
Yes, and that's one of the most common uses. Filter by the emotion that fits your content, listen to the most intense passages and, with video, create the clip right from that emotion, adjusting it word by word. Automatic clips also come labeled with a moment type, and emotion is one of them.
Which languages are supported?
The analysis runs on the transcript, so it works in all 90+ languages we transcribe. Emotion names show up in the language you use the app in: English, Portuguese or Spanish. That covers an English sermon, a Spanish-language interview or a Portuguese podcast.
Does emotion analysis work with audio only?
Yes. Emotions work the same way with audio, like a podcast, a recorded interview, a class or a testimonial. With audio you filter, favorite and download the passage as MP3. Vertical clips, reframing and burned-in captions need a video source, so those appear whenever you upload video.
Which plan includes emotion analysis?
All of them: Pro, Studio and Agency. Narrative hooks with an impact score, which help you pick the opening line of a video, are on Studio and Agency. Before you add a card, you can already see the result on your own material.