Better pacing
Tags help separate narration, urgent dialogue, quiet moments, and fast reactions so the audio does not feel flat.
🔒 Free tier data may be used to improve AI models. Upgrade Pro for 100% Privacy
AI emotional dubbing
Generate expressive AI voices from subtitle files.
Use ChatGPT or Gemini to automatically add emotion tags, then upload the tagged SRT into TTS For Free to generate natural AI speech.
AI voices often sound robotic when every subtitle line is read with the same pacing, emphasis, and emotional intensity. Emotion tags give the voice engine better direction before each line.
Tags help separate narration, urgent dialogue, quiet moments, and fast reactions so the audio does not feel flat.
A tagged subtitle can signal when a line should sound excited, angry, sad, whispered, or surprised.
Dialogue scenes become easier to follow when speakers do not all sound like the same neutral narrator.
Instead of adding hundreds of tags yourself, let ChatGPT or Gemini analyze context and insert them automatically.
This landing page reuses the existing SRT to Speech engine. The new layer is the guidance: prepare your subtitles with AI emotion tags first, then generate expressive speech.
Start with a video, scene, episode, course, or short-form clip.
Use Video to SRT or your own subtitle workflow to create an editable SRT file.
Optional: translate the SRT first if you are localizing content into another language.
Paste the SRT into ChatGPT or Gemini with the prompt below.
The assistant reads context and adds tags before dialogue while preserving timing.
Upload the modified SRT into the SRT to Speech engine on this page.
Create AI speech with more natural emotion, pacing, and performance cues.
Download the audio and merge it back with the original video in your editor.
The best workflow is not manually adding tags to every subtitle line. Use an assistant first, then review the SRT before generating speech.
Paste your SRT after this prompt. The AI will add emotion tags while preserving subtitle timing and formatting.
You are an expert subtitle editor and AI dubbing director. Task: Insert one emotion tag before each dialogue line in this SRT file. Allowed tags: [happy], [sad], [angry], [whisper], [excited], [narrator], [surprised], [laughing] Rules: 1. Preserve every SRT index number exactly. 2. Preserve every timestamp exactly. 3. Preserve line breaks and subtitle formatting. 4. Do not translate unless I explicitly ask you to translate. 5. Add only one emotion tag before each spoken subtitle text. 6. Choose tags based on context, punctuation, dialogue intent, and scene emotion. 7. Use [narrator] for neutral narration or exposition. 8. Return only the complete modified SRT. Do not add explanations. SRT:
Copy individual tags when you want manual edits, or play a quick browser preview to understand the intent of each tag.
Warm and positive
Use for relief, bright conversations, friendly narration, and optimistic scenes.
Quiet and hurt
Use for loss, regret, apology, farewell, or emotional memory.
Sharp and intense
Use for conflict, accusation, battle scenes, and strong frustration.
Soft and secretive
Use for suspense, secrets, fear, intimacy, or low-volume scenes.
Fast and energetic
Use for discovery, action, victory, anticipation, and enthusiastic dialogue.
Clear and steady
Use for exposition, documentary tone, recaps, and neutral storytelling.
Sudden reaction
Use when a character notices something unexpected or reacts quickly.
Playful and amused
Use for jokes, teasing, relieved laughter, or light character moments.
The same subtitle can produce very different voice output when the model receives emotional context before the line.
12 00:00:31,200 --> 00:00:33,000 I thought you were never coming back.
12 00:00:31,200 --> 00:00:33,000 [sad] I thought you were never coming back.
Different platforms solve different parts of dubbing. This comparison focuses on subtitle workflow and emotion control, not only voice quality.
| Feature | TTS For Free | ElevenLabs | Azure SSML | Google Gemini TTS |
|---|---|---|---|---|
| Emotion workflow | Tag-driven SRT workflow with AI prompt guidance | Strong voice quality; workflow depends on product/API setup | SSML styles on supported voices | Gemini TTS capability varies by model and integration |
| Subtitle workflow | Built around SRT upload, timing, and block review | Usually needs separate subtitle preparation | Powerful but more technical with SSML | Best paired with custom workflow or prompt preparation |
| AI dubbing | Good for subtitle-to-speech and synced voiceover prep | Strong for high-quality voice generation | Strong for enterprise speech workflows | Useful in AI-assisted prompt and generation workflows |
| Multi-speaker | Speaker mapping is available in SRT to Speech workflows | Available depending on workflow and plan | Possible with voice selection and SSML | Depends on model and implementation |
| Cost | Credit-based platform workflow | Subscription or usage-based pricing | Cloud usage pricing | Quota or API pricing depends on Google account |
| Ease of use | Simple if your content is already in SRT | Polished voice tools, separate subtitle prep may be needed | Very capable but technical | Flexible, but usually needs workflow setup |
Emotion-tagged subtitles are useful whenever neutral narration is not enough.
Do not manually tag hundreds of subtitle lines. Use ChatGPT or Gemini first, then generate speech from the tagged SRT.
Extract subtitles from your video with Video to SRT or another subtitle tool.
Optional: translate the SRT if you are localizing into another language.
Paste the provided prompt into ChatGPT or Gemini, then paste your SRT below it.
The assistant analyzes context and inserts tags before each dialogue line.
Review the result, then upload the modified SRT into TTS For Free.
Generate AI speech from the tagged subtitles.
Download the generated audio and combine it with your video in an editor.
Tip: if the AI adds too many strong emotions, ask it to use a more subtle, cinematic style.
If you do not have subtitles yet, start with Video to SRT. If you need subtitle translation before dubbing, use SRT Translation, then return here to generate expressive speech.
For the complete process from video and translation to speaker mapping, timing, and final mix, read the AI Dubbing workflow.
After ChatGPT or Gemini returns the modified subtitle file, upload it below. This is the same backend as SRT to Speech, presented here for emotional dubbing workflows.
Upload SRT, edit the content, map each speaker to a voice, then generate audio in a simpler step-by-step flow.
Usage details
Auto-detect [A], [B], then map each speaker to a voice.
A: Yes. You can paste an SRT file into ChatGPT with a clear prompt asking it to preserve timestamps and insert one emotion tag before each dialogue line.
A: Yes. Gemini can analyze subtitle context and add tags when you provide a strict prompt that preserves index numbers, timestamps, and formatting.
A: Emotion tags can improve pacing, emphasis, and performance cues when the selected voice and provider support the tag style used in the workflow.
A: For best consistency, use one clear tag per subtitle line. You can edit tags manually later if a scene needs a different emotion.
A: Yes. Review the generated SRT before upload, then change any tag that feels too strong, too subtle, or wrong for the scene.
A: Support depends on the selected voice and provider. Test a short scene first, then continue with the full subtitle file after you find a voice that responds well.
A: Yes, but split very long SRT files into manageable chunks when asking ChatGPT or Gemini to add tags, then review the result before generating speech.