Automate Zoom Meeting Summary

Data Sleek was grappling with the inefficiency and miscommunication often encountered during client meetings, particularly in a remote working environment. The core challenges to be addressed included:

• Automation Complexity: Developing a process to automatically identify, process, and save each meeting's content required nuanced logic and planning.
• Translation Accuracy: Converting audio to text across different languages and accents necessitated a highly accurate algorithm.
• Data Cleaning: Removing fillers and irrelevant information from raw speech without losing context was vital to streamline data processing.
• False Recording Prevention: A mechanism was needed to filter out empty or false recordings without losing essential content.
• Summarization Efficiency: Creating an algorithm to extract and present key points from human communication presented a unique challenge.
• Sensitive Content Handling: The tool had to recognize and omit private information while maintaining overall context and meaning.

The ultimate goal was to create a tool that could not only handle these challenges but also revolutionize the way Data Sleek engaged with clients. By automating the summarization of meetings, the tool would enable more effective collaboration, real-time engagement, and a significant reduction in misunderstandings and time loss. Addressing these problems required technological innovation paired with an intricate understanding of human communication, setting the stage for an ambitious and transformative project.

The solution for automating the summarization of meeting content at Data Sleek involved a careful selection of tools, each serving specific roles in the multi-stage process. Here's how the tools were applied:

AWS (Amazon Web Services): The core infrastructure provider, enabling data handling, storage, processing, and deployment of Lambda functions, integrating various services to form the backbone of the system.

AWS Transcribe: Utilized in the project to swiftly convert meeting audio files into text, AWS Transcribe's machine-learning capabilities ensured accuracy across multiple languages and dialects. Its seamless integration with other AWS services made it a key component in the transcription process, forming the foundational data for further analysis and summarization.

OpenAI: Leveraged for intelligent text summarization, OpenAI's models transformed large text documents into concise and relevant summaries, effectively capturing the main points of the meetings.

MySQL: Utilized for tracking each meeting's status and storing the transformation process details, from original audio to summarized text, including attendee’s name and date the meeting.

Dropbox: Chosen for secure storage of initial audio recordings, preparing them for processing.

Make.com: A key component for scheduling and coordination, ensuring automation between various process stages, such as audio conversion, text summarization, and duplicate avoidance.

Convertio: Used for converting original audio files into a suitable format for transcription, facilitating the smooth progression of the process.

Process Workflow:

1. Meeting End and Audio Saving: Immediate archiving of audio files in Dropbox upon meeting conclusion.
2. Duplicate Avoidance: Daily constraints to process unique meetings, managed through Make.com.
3. Audio Conversion and Storage: Conversion to mp3 format using Convertio, followed by storage in AWS S3.
4. Transcription Process: AWS Transcribe converted mp3 files into text, with MySQL linking original audio and transcript.
5. Data Cleaning: Utilized Lambda functions, Natural Language Toolkit (NLTK), and paraphrasing models to enhance readability and cost savings.
6. Text Summarization: OpenAI API summarized the cleaned text, storing the result in S3 and updating MySQL.
7. Automation and Scheduling: Make.com scheduled the Lambda functions for batch processing, automating the entire workflow.

These solutions came together to create a sophisticated, self-running system, transforming a complex process into an efficient one, enhancing client interactions, and setting a new standard for effective communication within Data Sleek.