Automating Vietnamese Meeting Minutes with STT + LLM APIs: A Technical Guide

In modern business environments, recording and processing information from meetings often consumes significant time and resources. The emergence of artificial intelligence has opened the door to automating meetings by combining Vietnamese STT APIs and LLM summarization. This article provides a detailed technical guide for building a system that generates accurate AI meeting minutes, enabling rapid integration into existing workflows.

Why Automate Vietnamese Meeting Minutes?

Manual note-taking is not only slow but also prone to missing critical information, especially in fast-paced meetings or those involving specialized terminology. Applying speech recognition and natural language processing (NLP) technologies converts speech into text instantly. Subsequently, a Large Language Model (LLM) analyzes the content, extracts key points, tasks, and assignees. This approach not only automates meetings but also ensures data integrity, allowing employees to focus on the discussion rather than worrying about note-taking.

Technical Architecture of the AI Meeting Minutes System

To build an effective system, you need to connect two main components: a Speech-to-Text (STT) service and a Language Model (LLM). Below is the recommended architecture:

1. Input Audio Capture and Processing

The first step is capturing the audio signal from the meeting. You can use a microphone array or dedicated recording hardware. The signal needs to be standardized in format (e.g., WAV, MP3) and an appropriate sampling rate. For online meetings, you can integrate audio capture SDKs from platforms like Zoom, Meet, or Teams.

2. Speech-to-Text Conversion via STT API

This is the critical step that determines the accuracy of the minutes. You need a Vietnamese STT API capable of handling natural speech, including cases where English is interspersed (code-switching).

AIVISION provides a Speech-to-Text API with features suitable for this need:

• Streaming support: Real-time speech recognition over WebSocket, allowing text to be displayed while the meeting is in progress.
• File processing: Convert audio files to text via REST API, suitable for processing recordings after the meeting.
• Word timestamps: Provides time markers for each word, helping to accurately identify who spoke when and which segments require attention.
• Accuracy: Trained on a large-scale Vietnamese dataset, AIVISION's model achieves an average Word Error Rate (WER) of 10.53% on internal test sets, including 3.60% on the standard read-speech FLEURS-vi dataset.

3. Analysis and Summarization with LLM

After obtaining raw text from the STT, you send this data to a Large Language Model (LLM) for processing. The LLM performs the following tasks:

• Noise filtering: Removes filler words, noise, or irrelevant statements.
• Content summarization: Condenses long text into key ideas.
• Action extraction: Identifies specific tasks, assignees, and deadlines.
• Formatting: Outputs the minutes in a clear structure, for example: "Discussion Points," "Decisions," "Action Items."

Practical Implementation Workflow

Here are the specific steps to deploy the AI meeting minutes system:

1. Set up API Key: Create an account and obtain an API Key from the management console.
2. Record the Meeting: Use hardware or software to record the entire meeting.
3. Call STT API: Send the audio file or stream to the STT endpoint. Receive raw text with timing information (timestamps).
4. Process Text: Clean the text if necessary and split it into segments suitable for the LLM's token limit.
5. Call LLM API: Send the processed text to the LLM API with a prompt clearly specifying the requirement to summarize and extract tasks.
6. Store and Share: Save the minutes to a document management system or send them directly to the email addresses of attendees.

Example Prompt for LLM Summarization

To achieve the best results from the LLM, you need to use a clear prompt. Here is an example:

Act as a professional secretary. Below is the raw transcript from a meeting:
[INSERT_TRANSCRIPT_HERE]

Requirements:
1. Summarize the main content of the meeting in 3-5 sentences.
2. List the decisions made.
3. Create a table of action items with columns: Task, Assignee, Deadline.
4. Use Vietnamese, with a professional and concise tone.

Benefits and Considerations for Deployment

Implementing this technology brings several benefits:

• Time savings: Eliminates manual note-taking and editing steps.
• Increased accuracy: Minimizes human errors during the note-taking process.
• Easy retrieval: Minutes are digitized and allow for quick keyword searching.

However, you should note:

• Audio quality: Ensure recording devices have good quality to optimize STT accuracy.
• Data security: Comply with information security regulations when processing internal company data.
• Final check: Always include a manual review step by a human before releasing official minutes, especially for important meetings.

Conclusion

Combining a Vietnamese STT API and LLM summarization is an effective solution to automate meetings and create high-quality AI meeting minutes. With strong natural language processing capabilities and high accuracy, solutions like those from AIVISION help businesses optimize workflows and enhance productivity.

If you are looking for a stable and easy-to-integrate solution, Start free with AIVISION's services to experience speech recognition and natural language processing technologies designed specifically for Vietnamese. For more details on APIs and technical consultation, please Contact the support team. You can also explore other in-depth articles at the Blog.

Frequently asked questions

How is a Vietnamese STT API different from standard recording tools?

An STT API does not just record audio; it converts speech into structured text and supports natural language processing, whereas recording tools only store raw audio files.

What factors affect the accuracy of AI meeting minutes?

Accuracy depends on the quality of the input audio, the complexity of specialized terminology, and the language processing capabilities of both the STT and LLM models.

Can this system be integrated into existing meeting software?

Yes, you can integrate STT and LLM APIs into online meeting platforms or project management software via REST or WebSocket.

Does AIVISION support English in Vietnamese meetings?

Yes, AIVISION's STT model supports code-switching, meaning it can naturally recognize English words interspersed within Vietnamese sentences.

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