Automated Video Interview ML/NLP Model
Budget: $3,000 – $5,000 USD
Project Brief for BERT Consultant
1. Project Objective
Develop a custom Automated Video Interview (AVI) model that evaluates candidates' personality traits (e.g., Big Five Personality traits) and competencies using advanced machine learning and natural language processing (NLP) techniques. The tool should streamline candidate assessment by analyzing verbal, paraverbal, and nonverbal cues from video interviews.
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2. Scope of Work
The consultant will handle the following:
1. Feature Engineering:
Extract and analyze:
Verbal Features: Words, phrases, sentiment, tone.
Paraverbal Features: Pitch, pace, and cadence of speech.
Nonverbal Features: Facial expressions, head movements, and gestures (if applicable).
Incorporate NLP techniques like BERT or RoBERTa for text-based feature extraction.
2. Model Development:
Develop machine learning models (e.g., Ridge Regression, Neural Networks) to predict personality traits and competencies.
Optimize model performance using cross-validation and hyperparameter tuning.
3. Ethical and Bias Considerations:
Ensure models meet legal requirements (e.g., Equal Employment Opportunity Commission guidelines).
Reduce subgroup biases using multi-penalty optimization or similar techniques.
4. Testing and Validation:
Validate the model for:
Test-retest reliability.
Convergent validity (correlation with human evaluators).
Criterion-related validity (correlation with job performance metrics).
5. Deployment:
Integrate the AVI system into a user-friendly platform for recruiters.
Ensure scalability for diverse job roles and industries.
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3. Deliverables
1. Processed feature dataset (using existing data provided by the client).
2. Working machine learning model with clear documentation.
3. Ethical and bias impact report.
4. Web-based or integrated AVI tool for recruiters.
4. Key Requirements
1. Technical Expertise:
Proficiency in NLP, ML, and video processing.
Familiarity with tools like Python, TensorFlow, PyTorch, and Scikit-learn.
2. Legal Compliance:
Compliance with data privacy laws (e.g., GDPR).
Adherence to legal guidelines for employment assessments.
3. Scalability:
Model must work for various job roles and industries.
4. Transparency:
Model must be explainable (e.g., why certain traits are detected).
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5. Timeline and Budget
Project Duration: 3 months.
Budget: Maximum of USD 4000
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1. Project Objective
Develop a custom Automated Video Interview (AVI) model that evaluates candidates' personality traits (e.g., Big Five Personality traits) and competencies using advanced machine learning and natural language processing (NLP) techniques. The tool should streamline candidate assessment by analyzing verbal, paraverbal, and nonverbal cues from video interviews.
---
2. Scope of Work
The consultant will handle the following:
1. Feature Engineering:
Extract and analyze:
Verbal Features: Words, phrases, sentiment, tone.
Paraverbal Features: Pitch, pace, and cadence of speech.
Nonverbal Features: Facial expressions, head movements, and gestures (if applicable).
Incorporate NLP techniques like BERT or RoBERTa for text-based feature extraction.
2. Model Development:
Develop machine learning models (e.g., Ridge Regression, Neural Networks) to predict personality traits and competencies.
Optimize model performance using cross-validation and hyperparameter tuning.
3. Ethical and Bias Considerations:
Ensure models meet legal requirements (e.g., Equal Employment Opportunity Commission guidelines).
Reduce subgroup biases using multi-penalty optimization or similar techniques.
4. Testing and Validation:
Validate the model for:
Test-retest reliability.
Convergent validity (correlation with human evaluators).
Criterion-related validity (correlation with job performance metrics).
5. Deployment:
Integrate the AVI system into a user-friendly platform for recruiters.
Ensure scalability for diverse job roles and industries.
---
3. Deliverables
1. Processed feature dataset (using existing data provided by the client).
2. Working machine learning model with clear documentation.
3. Ethical and bias impact report.
4. Web-based or integrated AVI tool for recruiters.
4. Key Requirements
1. Technical Expertise:
Proficiency in NLP, ML, and video processing.
Familiarity with tools like Python, TensorFlow, PyTorch, and Scikit-learn.
2. Legal Compliance:
Compliance with data privacy laws (e.g., GDPR).
Adherence to legal guidelines for employment assessments.
3. Scalability:
Model must work for various job roles and industries.
4. Transparency:
Model must be explainable (e.g., why certain traits are detected).
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5. Timeline and Budget
Project Duration: 3 months.
Budget: Maximum of USD 4000
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