AI-Powered Humor Detection for YouTube Videos

Cascade Gate v8 Reddit-pretrained Val AUC 0.823 ONNX INT8 <3ms

๐ŸŽฌ Try it on a YouTube Video

Paste any YouTube URL and our AI will analyze the funniness across the whole video.

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๐ŸŽค Classic Comedy ๐Ÿ“บ Stand-up Set ๐ŸŒŸ First YouTube Vid ๐Ÿ˜‚ Try This ๐ŸŽ™๏ธ MKBHD ๐Ÿ’ป Linus Tech
๐ŸŽฅ
Paste a YouTube URL to load
Analyzing video...

๐ŸŽฏ Analysis Results

Overall Humor Score
0.00
Analyzing...
Peak Score
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Funny Segments
0/20
Avg Score
0.00
Variance
ยฑ0.00

๐Ÿ“ˆ Per-Segment Humor Timeline

Loading transcript...

๐Ÿค– How It Works

HaHaScore Cascade v10 uses a multimodal AI architecture that fuses text + audio cues:

๐Ÿ“š
Reddit Pretrain
DistilBERT trained on 30K jokes for humor-style priors
๐ŸŽš๏ธ
Audio + Text Fusion
Cascade Gate architecture with cross-modal attention
โšก
Fast ONNX INT8
2.9 MB model, ~3ms CPU inference
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Segment Analysis
20 segments per video with per-segment funniness scores

๐Ÿ’ป Use the Model in Your Code

import onnxruntime as ort
import numpy as np
from huggingface_hub import hf_hub_download

# Load model
model_path = hf_hub_download(
    repo_id="Hayasuki/hahascore-cascade-v10",
    filename="v10_cascade_int8.onnx"
)
session = ort.InferenceSession(model_path)

# Run inference
text = np.random.randn(1, 20, 768).astype(np.float32)
audio = np.random.randn(1, 20, 791).astype(np.float32)
cross = np.zeros((1, 20, 16), dtype=np.float32)

scores, conf, gate = session.run(None, {
    'text': text, 'audio': audio, 'cross': cross
})
print(f"Average humor: {scores.mean():.3f}")