Speech Analysis ML Model for Hypertension Screening
Budget: ₹1,500 – ₹12,500 INR
Project Title:
Development of an Age- and Gender-Specific Machine Learning Model for Hypertension Screening via Speech Analysis
Project Description:
I need a freelancer with expertise in machine learning, speech processing, and health analytics to improve the accuracy of an existing hypertension screening model that uses acoustic speech analysis. The goal is to develop an age- and gender-specific model with enhanced performance.
Project Requirements:
Model Improvement: Optimize the existing machine learning model by incorporating age and gender as key factors.
Feature Engineering: Extract and refine acoustic features from speech data to improve classification accuracy.
Algorithm Selection: Experiment with different machine learning techniques (e.g., SVM, Random Forest, Deep Learning models) to determine the best-performing model.
Data Handling: Implement oversampling (SMOTE) or other techniques to handle class imbalances in the dataset.
Performance Evaluation: Use leave-one-subject-out (LOSO) cross-validation and metrics like accuracy, specificity, and sensitivity to assess model performance.
Deployment: Provide a working model with documentation and code in Python (preferably using Scikit-Learn, TensorFlow, or PyTorch).
Preferred Skills:
Strong background in machine learning & deep learning
Experience with speech signal processing (Librosa, Praat, OpenSMILE, etc.)
Knowledge of medical data analysis and bioinformatics
Proficiency in Python (Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy)
Ability to preprocess, clean, and augment speech datasets
Deliverables:
Trained machine learning model optimized for accuracy
Python code with comments explaining key steps
Model evaluation report with performance metrics
Optional: Deployment-ready API for real-world use
Looking forward to working with an expert in this field!
Development of an Age- and Gender-Specific Machine Learning Model for Hypertension Screening via Speech Analysis
Project Description:
I need a freelancer with expertise in machine learning, speech processing, and health analytics to improve the accuracy of an existing hypertension screening model that uses acoustic speech analysis. The goal is to develop an age- and gender-specific model with enhanced performance.
Project Requirements:
Model Improvement: Optimize the existing machine learning model by incorporating age and gender as key factors.
Feature Engineering: Extract and refine acoustic features from speech data to improve classification accuracy.
Algorithm Selection: Experiment with different machine learning techniques (e.g., SVM, Random Forest, Deep Learning models) to determine the best-performing model.
Data Handling: Implement oversampling (SMOTE) or other techniques to handle class imbalances in the dataset.
Performance Evaluation: Use leave-one-subject-out (LOSO) cross-validation and metrics like accuracy, specificity, and sensitivity to assess model performance.
Deployment: Provide a working model with documentation and code in Python (preferably using Scikit-Learn, TensorFlow, or PyTorch).
Preferred Skills:
Strong background in machine learning & deep learning
Experience with speech signal processing (Librosa, Praat, OpenSMILE, etc.)
Knowledge of medical data analysis and bioinformatics
Proficiency in Python (Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy)
Ability to preprocess, clean, and augment speech datasets
Deliverables:
Trained machine learning model optimized for accuracy
Python code with comments explaining key steps
Model evaluation report with performance metrics
Optional: Deployment-ready API for real-world use
Looking forward to working with an expert in this field!