# ExciteMeter Model

## Overview

The **ExciteMeter** model is designed to analyze audio inputs and provide an "Excitement Score" indicating how exciting the audio is. This model can be used for various applications such as content analysis, media production, and user engagement evaluation.

## Model Details

- **Architecture**: This model is based on a custom neural network architecture designed for audio signal processing. It takes in raw audio data, processes it through several convolutional and recurrent layers, and outputs a single excitement score.
- **Input**: The model accepts audio files in `.wav` format. It processes audio data sampled at 16 kHz.
- **Output**: A single scalar value representing the "Excitement Score," where a higher value indicates more excitement.

## Usage

### Installation

To use the ExciteMeter model, first ensure you have the required dependencies installed:

```bash
pip install -r requirements.txt