Gender Voice Recognition

The client, a call center service provider, faced significant operational challenges due to a high volume of fake calls that disrupted workflow and threatened user safety. Without an effective means to filter these calls, both efficiency and security were compromised. To address this, we developed an AI-driven solution using voice recognition technology. This solution analyzes incoming calls, determines caller gender, and routes calls accordingly, thereby enhancing efficiency and safety.


The client was inundated with fake calls during operational hours, which not only disrupted workflow but also posed a threat to user safety. The lack of an effective filtering mechanism compromised both efficiency and security, making it difficult for the call center to function optimally.


To tackle the client’s problem, we devised a multi-faceted AI solution:


  1. Real-time Voice Analysis:
    • The system listens to incoming calls in real-time.
    • It uses trained AI models to recognize the caller’s gender based on voice patterns.


2. Gender-based Call Routing:

    • Calls from male callers are routed to a general line where any available operator can assist them.
    • Calls from female callers are directed to a virtual women’s police station, staffed by specially trained female officers.

3. Filtering Fake Calls:

    • The system filters out fake calls by analyzing call patterns and behaviors, reducing the harassment faced by recipients and improving the overall safety and efficiency of the call center.

Features & Benefits

Gender-based Call Routing

The AI model identifies the caller’s gender and routes the call accordingly. Male callers are directed to a general line, while female callers are connected directly to the virtual police station for women.

Reduced Harassment

By automatically filtering out fake calls, the solution significantly reduces harassment faced by female officers, creating a safer and more comfortable environment for genuine callers.

Efficient Call Handling

Real-time processing of calls within 20 seconds ensures prompt and effective handling of incoming communications, improving overall operational efficiency

Technologies Used to Build the Solution

Python, TensorFlow, Flask API, Voice Recognition, Deployment