audio_path string | text string | text_with_tags string | frame_labels list | segments list | has_transition bool | voice string | dominant_emotion string |
|---|---|---|---|---|---|---|---|
output/temporal_dataset/audio/audio_154739.wav | Graduation day! But I'll miss everyone. | [happy] Graduation day! [sad] But I'll miss everyone. | [
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output/temporal_dataset/audio/audio_199312.wav | You need to fix this immediately! | [angry] You need to fix this immediately! | [
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output/temporal_dataset/audio/audio_207963.wav | The concert was amazing. Best night ever! | [neutral] The concert was amazing. [happy] Best night ever! | [
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output/temporal_dataset/audio/audio_329164.wav | She said yes! I couldn't believe it! | [happy] She said yes! [surprise] I couldn't believe it! | [
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output/temporal_dataset/audio/audio_858179.wav | The cat ran away. She came back! | [sad] The cat ran away. [happy] She came back! | [
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output/temporal_dataset/audio/audio_807189.wav | The train arrived late. But we made it anyway! | [neutral] The train arrived late. [happy] But we made it anyway! | [
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output/temporal_dataset/audio/audio_922859.wav | I forgot my lines. No one seemed to notice. | [sad] I forgot my lines. [neutral] No one seemed to notice. | [
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output/temporal_dataset/audio/audio_871084.wav | I wish things were different. | [sad] I wish things were different. | [
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output/temporal_dataset/audio/audio_326147.wav | We raised one million dollars! In just one day! | [happy] We raised one million dollars! [surprise] In just one day! | [
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output/temporal_dataset/audio/audio_426170.wav | The data has been updated in the system. | The data has been updated in the system. | [
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output/temporal_dataset/audio/audio_873349.wav | The data has been updated in the system. | The data has been updated in the system. | [
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output/temporal_dataset/audio/audio_874224.wav | The store is on fire. Everyone evacuate! | [neutral] The store is on fire. [fear] Everyone evacuate! | [
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output/temporal_dataset/audio/audio_487282.wav | That's the final straw! I'm done. | [angry] That's the final straw! [sad] I'm done. | [
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output/temporal_dataset/audio/audio_259295.wav | Unbelievable! Really? | [surprise] Unbelievable! Really? | [
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output/temporal_dataset/audio/audio_132352.wav | I'm delighted with the outcome! | [happy] I'm delighted with the outcome! | [
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output/temporal_dataset/audio/audio_944956.wav | I'm delighted with the outcome! | [happy] I'm delighted with the outcome! | [
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output/temporal_dataset/audio/audio_556932.wav | The meeting is scheduled for three o'clock. | [neutral] The meeting is scheduled for three o'clock. | [
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output/temporal_dataset/audio/audio_467574.wav | The relationship ended. We're still friends though. | [sad] The relationship ended. [neutral] We're still friends though. | [
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output/temporal_dataset/audio/audio_586075.wav | The meeting is scheduled for three o'clock. | [neutral] The meeting is scheduled for three o'clock. | [
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output/temporal_dataset/audio/audio_934953.wav | The economy is improving. Jobs are coming back. | [neutral] The economy is improving. [happy] Jobs are coming back. | [
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output/temporal_dataset/audio/audio_353894.wav | The power went out. What was that noise? | [neutral] The power went out. [fear] What was that noise? | [
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output/temporal_dataset/audio/audio_511233.wav | The memories keep coming back. | [sad] The memories keep coming back. | [
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output/temporal_dataset/audio/audio_582789.wav | We'll schedule another call next week. | We'll schedule another call next week. | [
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output/temporal_dataset/audio/audio_160227.wav | The training session is mandatory. | The training session is mandatory. | [
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output/temporal_dataset/audio/audio_487623.wav | A tornado! It's heading this way! | [surprise] A tornado! [fear] It's heading this way! | [
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output/temporal_dataset/audio/audio_568969.wav | Please confirm your attendance by email. | Please confirm your attendance by email. | [
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output/temporal_dataset/audio/audio_177934.wav | I'm terrified of the results. | [fear] I'm terrified of the results. | [
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output/temporal_dataset/audio/audio_678998.wav | Stop this at once! | [angry] Stop this at once! | [
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output/temporal_dataset/audio/audio_206606.wav | Please submit your feedback by Friday. | Please submit your feedback by Friday. | [
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output/temporal_dataset/audio/audio_724156.wav | I missed the last bus and now I have to walk home alone. | [sad] I missed the last bus and now I have to walk home alone. | [
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output/temporal_dataset/audio/audio_879995.wav | Unbelievable! Really? | [surprise] Unbelievable! Really? | [
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output/temporal_dataset/audio/audio_493152.wav | The memories keep coming back. | [sad] The memories keep coming back. | [
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output/temporal_dataset/audio/audio_110665.wav | How dare you ignore my requests! | [angry] How dare you ignore my requests! | [
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output/temporal_dataset/audio/audio_649342.wav | What if everything goes wrong? | [fear] What if everything goes wrong? | [
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output/temporal_dataset/audio/audio_362479.wav | The diagnosis is confirmed. But treatment is available. | [neutral] The diagnosis is confirmed. [sad] But treatment is available. | [
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output/temporal_dataset/audio/audio_408396.wav | This makes me so happy! | [happy] This makes me so happy! | [
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output/temporal_dataset/audio/audio_461239.wav | We adopted a puppy! Wait, the landlord said no. | [happy] We adopted a puppy! [sad] Wait, the landlord said no. | [
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output/temporal_dataset/audio/audio_545175.wav | We won the championship! But the captain got injured. | [happy] We won the championship! [sad] But the captain got injured. | [
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output/temporal_dataset/audio/audio_997409.wav | The book is finally published! But my mentor passed away. | [happy] The book is finally published! [sad] But my mentor passed away. | [
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output/temporal_dataset/audio/audio_834904.wav | My phone died. Good thing I had a backup. | [sad] My phone died. [happy] Good thing I had a backup. | [
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output/temporal_dataset/audio/audio_253080.wav | This is intolerable behavior! | [angry] This is intolerable behavior! | [
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output/temporal_dataset/audio/audio_941423.wav | That's enough! Let's calm down and discuss. | [angry] That's enough! [neutral] Let's calm down and discuss. | [
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output/temporal_dataset/audio/audio_182480.wav | The movie started slow. But the ending was perfect! | [neutral] The movie started slow. [happy] But the ending was perfect! | [
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output/temporal_dataset/audio/audio_645414.wav | The data looks strange. It's a breakthrough! | [neutral] The data looks strange. [surprise] It's a breakthrough! | [
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output/temporal_dataset/audio/audio_766536.wav | This is a standard configuration. | [neutral] This is a standard configuration. | [
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output/temporal_dataset/audio/audio_457592.wav | Something bad is going to happen! | [fear] Something bad is going to happen! | [
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output/temporal_dataset/audio/audio_763934.wav | The diagnosis is confirmed. But treatment is available. | [neutral] The diagnosis is confirmed. [sad] But treatment is available. | [
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output/temporal_dataset/audio/audio_403906.wav | We'll proceed with the standard procedure. | [neutral] We'll proceed with the standard procedure. | [
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output/temporal_dataset/audio/audio_652483.wav | Don't go in there. It's a trap! | [fear] Don't go in there. [angry] It's a trap! | [
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output/temporal_dataset/audio/audio_287936.wav | We adopted a puppy! Wait, the landlord said no. | [happy] We adopted a puppy! [sad] Wait, the landlord said no. | [
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output/temporal_dataset/audio/audio_255836.wav | Graduation day! But I'll miss everyone. | [happy] Graduation day! [sad] But I'll miss everyone. | [
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output/temporal_dataset/audio/audio_235552.wav | The survey will be sent out next week. | The survey will be sent out next week. | [
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output/temporal_dataset/audio/audio_754213.wav | I've had enough of this nonsense! | [angry] I've had enough of this nonsense! | [
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output/temporal_dataset/audio/audio_754717.wav | Please submit your timesheet by Friday. | Please submit your timesheet by Friday. | [
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output/temporal_dataset/audio/audio_133470.wav | The doctor walked in. He had the test results. | [neutral] The doctor walked in. [surprise] He had the test results. | [
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End of preview. Expand in Data Studio
VoxTral Emotion Temporal Dataset
Dataset for training emotion transition detection in speech. ~500 clips with frame-level emotion annotations at 20ms resolution.
Overview
| Property | Value |
|---|---|
| Clips | ~500 |
| Sample Rate | 16000 Hz |
| Frame Resolution | 20ms |
| Emotions | 6 (neutral, happy, angry, sad, surprise, fear) |
Clip Distribution
- Single Emotion (40%): One emotion throughout
- Transitions (40%): Emotion changes mid-sentence (2-3 segments)
- No Emotion (20%): Flat neutral (teaches model NOT to hallucinate)
Splits
- train: 70%
- validation: 15%
- test: 15%
Data Format
from datasets import load_dataset
ds = load_dataset("MrlolDev/voxtral-emotion-temporal")
# Example item
item = ds["train"][0]
# {
# "audio_path": "audio/audio_000001.wav",
# "text": "The meeting starts at nine. But nobody ever shows up on time.",
# "text_with_tags": "[neutral] The meeting starts at nine. [angry] But nobody ever shows up on time.",
# "frame_labels": [0, 0, 0, ..., 2, 2, 2, ...], # 50 items for ~1s audio
# "segments": [
# {"emotion": "neutral", "char_start": 0, "char_end": 29},
# {"emotion": "angry", "char_start": 29, "char_end": 999}
# ],
# "has_transition": True,
# "voice": "voice_reference_1.wav",
# "dominant_emotion": "angry"
# }
Running Locally
# Install dependencies
pip install -r requirements.txt
# Generate dataset
python generate_temporal_dataset.py --num_clips 500 --output_dir ./output
# Generate and push to Hub
python generate_temporal_dataset.py --push_to_hub --token $HF_TOKEN
Arguments
| Argument | Default | Description |
|---|---|---|
--num_clips |
500 | Number of clips to generate |
--output_dir |
output/temporal_dataset | Output directory |
--push_to_hub |
False | Push to HuggingFace |
--hub_repo_id |
MrlolDev/voxtral-emotion-temporal | Target repo |
--token |
None | HF token (or set HF_TOKEN env) |
Models Used
- Fish Audio S2 Pro: Text-to-speech with character-level timestamps
- SenseVoice: Emotion detection (optional quality filter, currently disabled)
Directory Structure
output/temporal_dataset/
├── audio/
│ ├── audio_000001.wav
│ ├── audio_000002.wav
│ └── ...
├── metadata.json
└── dataset_info.json
Emotion Index Mapping
0: neutral
1: happy
2: angry
3: sad
4: surprise
5: fear
Citation
@dataset{voxtral-emotion-temporal,
author = {MrlolDev},
title = {VoxTral Emotion Temporal Dataset},
year = {2025},
publisher = {HuggingFace},
url = {https://huggingface.co/datasets/MrlolDev/voxtral-emotion-temporal}
}
License
MIT
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