AI Chat-Bot and Calls Analysis with OpenAI and PyTorch
AI Chat-Bot and Calls Analysis with OpenAI and PyTorch
AI solution for communication and call analysis in educational camps
April 15, 2024
5 minutes read
SUMMARY
The client needed to analyze and understand the effectiveness of their employees' communication with customers and automate this process. It was crucial to assess how well the employees adhered to the sales script. By implementing an AI-driven solution, the client aimed to gain insights into the quality of interactions and ensure consistent delivery of the sales script, enhancing overall customer engagement and sales performance.
Additionally, a critical requirement was the precision in the information provided by the chatbot. Accurate and up-to-date data needed to be delivered to ensure that parents and participants received reliable answers to their questions. This necessitated the integration of a dynamic content update system within the chatbot, enabling real-time data synchronization with the camp’s administrative databases.
Furthermore, to cater to a diverse clientele, the chatbot was designed to support multiple languages. This multilingual capability was crucial to broaden the camp's reach and effectively communicate with non-English speaking parents and participants, thus enhancing user experience and inclusivity. This feature employed advanced natural language processing techniques to understand and generate responses in several languages, ensuring clear and concise communication across different cultural backgrounds.
TECH STACK
PyTorch
GPT
Python
DELIVERY TIMELINE
1 Week
Solution Architecture Design
2 Weeks
OpenAI Chat-Bot Development & Integration
2 Weeks
Calls Analysis Model Development
1 Week
Deployment & Testing
TECH CHALLENGE
Significant hurdle was the integration of the AI chatbot with social media platforms such as Instagram, Facebook, and WhatsApp. These platforms, managed by Meta, require rigorous compliance and security checks before allowing third-party integrations. This necessitated establishing a robust line of communication with Meta to navigate their approval process effectively, ensuring that our integration met all required standards and protocols to safeguard user data and interactions.
Client provided a repository of call recordings, these were not accompanied by assessments of interaction quality. Consequently, our team was tasked with meticulously listening to each recording to evaluate the conversations based on several parameters including tone, clarity, and conflict presence. Following this initial assessment, we collaborated closely with the client to calibrate these evaluations, aligning them with specific metrics and expectations set forth by the client. This foundational work was crucial for training our AI model to accurately reflect and enhance the camp's communication standards.
SOLUTION
For the chatbot, we leveraged the OpenAI Assistant to create a responsive and versatile communication tool. This bot was integrated across multiple platforms including Telegram, Facebook, WhatsApp, and Instagram, enabling seamless interactions with camp participants and their parents. The bot provided timely responses to queries, enhancing customer experience and operational efficiency.
The second part of the solution involved a proprietary AI model designed to analyze call quality and detect conflict levels in conversations. This model was integrated into Telegram, where staff could upload call recordings and receive instant feedback on the interaction quality. Initially, the audio recordings were converted into text using OpenAI's Whisper model, a robust and accurate speech-to-text converter. Following transcription, the text underwent detailed language processing to assess tone and context effectively. After the preprocessing steps, the core analysis was conducted using a custom-built neural network based on Long Short-Term Memory (LSTM) architecture. This network was specifically trained to identify nuances in conversation that indicate conflict levels and overall communication quality. Using advanced audio processing techniques and neural network analysis, the system provided detailed assessments that helped improve staff training and conflict resolution strategies, ensuring more effective and harmonious interactions in the camp environment.
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