Update README.md

README.md

@@ -3,15 +3,21 @@ license: apache-2.0
 language:
 - en
 tags:
-- infant-cry-classification
+- baby-cry-classification
 - machine-learning
 - audio-analysis
+- baby-cry-classification
 - signal-processing
 - acoustic-feature-extraction
 - audio-classification
 - speech-recognition
 ---
-# Infant Cry Classifier
+# Baby Cry Classifier
+
+<p align="center">
+<!-- Smaller size image -->
+<img src="https://huggingface.co/foduucom/infant-cry-classification/resolve/main/Baby-cry.jpg" alt="Image" style="width:500px; height:300px;">
+</p>
 
 ## Table of Contents
 1. [Introduction](#introduction)
@@ -27,53 +33,53 @@ tags:
 
 ## Introduction
 
-The Infant Cry Classifier is an advanced machine learning model designed to analyze and categorize different types of infant cries. This innovative tool aims to assist parents, caregivers, and healthcare professionals in understanding and responding to infants' needs more effectively.
+The Baby Cry Classifier is an advanced machine learning model designed to analyze and categorize different types of baby cries. This innovative tool aims to assist parents, caregivers, and healthcare professionals in understanding and responding to babys' needs more effectively.
 
 ## Problem Statement
 
-Interpreting an infant's cries can be challenging, especially for new parents or in high-stress situations. Babies communicate their needs primarily through crying, but distinguishing between different types of cries (e.g., hunger, discomfort, tiredness) can be difficult. This uncertainty can lead to:
+Interpreting an baby's cries can be challenging, especially for new parents or in high-stress situations. Babies communicate their needs primarily through crying, but distinguishing between different types of cries (e.g., hunger, discomfort, tiredness) can be difficult. This uncertainty can lead to:
 
 1. Increased stress for parents and caregivers
-2. Delayed response to the infant's needs
+2. Delayed response to the baby's needs
 3. Potential misinterpretation of the baby's requirements
 
 ## Solution
 
-Our Infant Cry Classifier addresses these challenges by:
+Our baby Cry Classifier addresses these challenges by:
 
-1. Analyzing audio recordings of infant cries
+1. Analyzing audio recordings of baby cries
 2. Extracting relevant acoustic features
 3. Classifying the cry into predefined categories (e.g., belly pain, burping, discomfort, hunger, tiredness)
 
 ## Importance and Need
 
-### 1. Enhanced Infant Care
+### 1. Enhanced baby Care
 
-By accurately identifying the reason behind an infant's cry, caregivers can respond more promptly and appropriately to the baby's needs. This can lead to:
+By accurately identifying the reason behind an baby's cry, caregivers can respond more promptly and appropriately to the baby's needs. This can lead to:
 
-- Improved infant comfort and well-being
-- Reduced stress for both the infant and caregiver
+- Improved baby comfort and well-being
+- Reduced stress for both the baby and caregiver
 - Better overall care and nurturing
 
 ### 2. Medical Applications
 
-In healthcare settings, the Infant Cry Classifier can be a useful diagnostic tool:
+In healthcare settings, the baby Cry Classifier can be a useful diagnostic tool:
 
 - Assisting pediatricians in identifying potential health issues
-- Supporting early detection of certain conditions that may affect an infant's cry patterns
+- Supporting early detection of certain conditions that may affect an baby's cry patterns
 - Providing objective data to complement clinical observations
 
 ### 3. Research Opportunities
 
 This model opens up new avenues for research in:
 
-- Infant communication and development
+- baby communication and development
 - Early childhood psychology
-- Acoustic analysis of infant vocalizations
+- Acoustic analysis of baby vocalizations
 
 ## How It Works
 
-1. **Data Collection**: The model is trained on infant cry audio samples, carefully labeled with their corresponding causes.
+1. **Data Collection**: The model is trained on baby cry audio samples, carefully labeled with their corresponding causes.
 
 2. **Feature Extraction**: Advanced signal processing techniques are used to extract relevant acoustic features from the audio samples.
 
@@ -95,8 +101,8 @@ This model opens up new avenues for research in:
 
 1. Clone this repository:
    ```bash
-   git clone https://huggingface.co/nehulagrawal/infant-cry-classification   
-   cd infant-cry-classifier
+   git clone https://huggingface.co/nehulagrawal/baby-cry-classification   
+   cd baby-cry-classifier
    ```
 
 2. Download the pre-trained model files:
@@ -174,6 +180,31 @@ result = predict_cry(file_path)
 print(f"Predicted cry type: {result}")
 ```
 
+## Model Performance
+
+Model Performance
+The baby Cry Classifier has undergone extensive testing to evaluate its effectiveness. Here's an overview of its performance:
+Accuracy Metrics:
+
+      class     precision    recall   f1-score
+
+           0       0.00      0.00      0.00         
+           1       0.67      0.67      0.67         
+           2       0.75      0.33      0.46        
+           3       0.50      0.43      0.46         
+           4       0.25      0.50      0.33         
+
+    accuracy                           0.38        
+   macro avg       0.43      0.39      0.38        
+weighted avg       0.51      0.38      0.41       
+
+Overall Accuracy: 
+
+Accuracy: 0.38461538461538464
+Precision: 0.4333333333333333
+Recall: 0.38571428571428573
+F1 Score: 0.38461538461538464
+
 ### Integration
 
 You can integrate this model into your own applications, such as:
@@ -200,7 +231,7 @@ For inquiries and contributions, please contact us at [email protected].
 @ModelCard{
     author       = {Nehul Agrawal and
                               Priyal Mehta},
-    title         = {Infant Cry Classifier},
+    title         = {baby Cry Classifier},
     year           = {2024}
 }
 ```