Emous V1 !free! -

Input Streams │ ├─► Video Module (FaceNet-based) ├─► Audio Module (wav2vec2 fine-tuned) └─► Text Module (DistilBERT) │ ▼ Fusion Layer (Attention-based) │ ▼ Emotion Predictor (Softmax over 7 classes) │ ▼ [JSON Output] "emotion": "joy", "confidence": 0.87

Instead of a simple "Positive/Negative" binary, emous v1 outputs an 8-dimensional affect vector. This allows developers to map input text to complex emotional states such as Melancholy , Mania , Resolve , or Apathy . emous v1

: New software developed using modern tools but styled with the pixelated charm of the 80s and 90s. Key Features of EmuOS v1.0 Key Features of EmuOS v1

The name "emous" is derived from the suffix -emous (meaning "full of") and the root emotion , signifying a system built to be "full of feeling" while remaining structurally simple. | Metric | Value | |--------|-------| | Accuracy

Since "emous" implies a focus on emotion, sentiment, or a minimalistic state of being, this write-up frames it as a lightweight, open-source sentiment analysis framework or a digital art protocol. Adjust the technical specifics as needed to fit your actual project.

| Metric | Value | |--------|-------| | Accuracy (on RAF-DB + IEMOCAP) | 84.3% | | Latency (full pipeline) | 45ms (M1 CPU) / 22ms (NVIDIA T4) | | Model Size | 14.8 MB | | RAM Usage | ~180 MB | | Power Draw | 1.2W (inference on Raspberry Pi 4) |