DreamScribe

DreamScribe is an interactive AI project that captures spoken dream input, analyzes emotions using NLP, calculates surrealism scores, and visualizes data through Python Turtle and R analytics.

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Features

• Speech-to-Text: Captures your voice using SpeechRecognition
• Emotion Analysis: Extracts Happy, Sad, Angry, Fear, and Surprise scores via text2emotion
• SER (Speech Emotion Recognition): Analyzes vocal tone using librosa
• Generative Art: Visualizes your dream mood using Python Turtle
• R Analytics: Generates professional emotion trends and surrealism histograms

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Installation & Setup

1. Fork & Clone

• Fork this repository to your own GitHub account
• Open your terminal (Git Bash or PowerShell) and clone it:

git clone https://github.com/your-username/DreamScribe.git
cd DreamScribe

2. Python Environment (3.13 Compatible)

Create a virtual environment to keep your dependencies clean and avoid path conflicts:

Windows (PowerShell):

python -m venv .venv
.\.venv\Scripts\Activate.ps1

Windows (Git Bash):

python -m venv .venv
source .venv/Scripts/activate

3. Install Dependencies

Install all required libraries, including the specific fixes for Python 3.13 (legacy-cgi) and text2emotion (emoji==1.7.0):

pip install -r requirements.txt

4. Setup NLP Data

Run this one-liner to download the necessary NLTK datasets for emotion analysis:

python -c "import nltk; nltk.download('punkt'); nltk.download('wordnet')"

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How to Run

Step 1: Record Your Dream

Run the main Python script. When prompted, speak clearly into your microphone for 7 seconds:

python main.py

• The script will log your data to dream_diary.csv
• Your dream art will be drawn with Turtle

Step 2: Analyze in R

Once you have logged dreams, run the R script to generate your trend charts.

Using Git Bash:

/c/Program\ Files/R/R-4.4.x/bin/Rscript.exe R_analysis.R

(Replace R-4.4.x with your actual version, e.g., R-4.4.2)

Using PowerShell:

& "C:\Program Files\R\R-4.4.x\bin\Rscript.exe" R_analysis.R

(Replace R-4.4.x with your actual version, e.g., R-4.4.2)

Step 3: View Results

Open the generated files in your project folder to see your data:

• avg_emotion_plot.png - Bar chart of average emotions
• surrealism_hist.png - Histogram of dream wildness
• Rplots.pdf - Combined analysis report

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Troubleshooting

Issue	Solution
ModuleNotFoundError: 'cgi'	This project uses legacy-cgi to remain compatible with Python 3.13
AttributeError: 'UNICODE_EMOJI'	This is fixed by using emoji==1.7.0. Do not upgrade the emoji library
Rscript not recognized	Ensure you are using the full path to your R installation as shown in the run steps above