Automating Meeting Minutes from Recordings: Combining Vietnamese STT and LLM

In modern business environments, recording meetings has become a standard practice to ensure no critical information is missed. However, listening to hours of audio and manually typing out key points is time-consuming and prone to errors. This article outlines the technical workflow for automating meeting minutes, combining speech recognition (Vietnamese STT) and large language models (LLM summarization) to create accurate, structured, and ready-to-use documents.

Why Automate Meeting Minutes?

Before diving into the technical details, consider the reality: a 60-minute meeting typically generates between 8,000 and 10,000 words. On average, it takes a person 2 to 3 hours to listen back and compile this into a concise document. This not only slows down project progress but also leads to employee fatigue.

Implementing AI meeting minutes addresses two core issues:

• Speed: Converts speech to text in real-time or near real-time.
• Contextual Accuracy: AI does more than just listen; it understands context to filter out noise, fill in gaps, and summarize key points.

Technical Workflow: Combining STT and LLM

To build an effective automation system, you need to integrate two main components: a Speech-to-Text (STT) model and a Large Language Model (LLM).

Step 1: Audio Processing and Vietnamese STT

The first and most critical step is converting audio files into text strings. For Vietnamese, this presents a significant challenge due to the language's tonal nature, compound words, and the frequent code-switching with English in business meetings.

A robust STT system must meet the following criteria:

• Code-switching support: Accurately identifies English terms interspersed within Vietnamese sentences.
• Word Timestamps: Attaches a time marker to each word, allowing users to easily locate specific moments in the recording for verification.
• Multi-media processing: Handles both uploaded files (via REST API) and live streams (via WebSocket) to serve both online and offline meetings.

At AIVISION, the STT technology is designed specifically for Vietnamese, handling both standard read speech and the natural speech patterns found in real-world meeting environments.

Step 2: Text Cleaning and Normalization

Raw output from STT often contains filler words, incomplete sentences, or spelling errors caused by audio noise. Before feeding the text into an LLM, it needs to be cleaned. Basic steps include:

• Removing non-meaningful filler words (such as "uh," "um," or "so") if they appear too frequently.
• Standardizing the spelling of technical terms.
• Performing Speaker Diarization (if supported by the system) to clearly identify who said what.

Step 3: LLM Summarization and Structuring

This step adds the most value. Instead of having a long block of raw text, LLM summarization helps organize the content into a logical structure.

By providing appropriate prompts, an LLM can:

1. Summarize key points: Condense lengthy discussions into concise bullet points.
2. Extract Action Items: Clearly identify tasks that need to be done, who is responsible, and the deadlines.
3. Highlight Decisions: List important decisions that were reached during the meeting.

Example Prompt:

"Summarize the following meeting. Extract a list of decisions made and tasks to be performed (including the responsible person and deadline). Present the results in a Markdown table."

The result is a clear table, replacing the need to read the entire raw transcript:

Decision	Responsible Person	Deadline
Update Q3 roadmap	Product Team	Oct 15
Submit financial report	Tuan	Oct 20

Benefits of Using a Specialized Solution

Many businesses tend to use general-purpose STT tools. Tuy nhiên, đối với tiếng Việt, việc sử dụng công nghệ được huấn luyện sâu cho ngôn ngữ bản địa mang lại hiệu quả cao.

AIVISION has built a large-scale Vietnamese database and deployed AI models optimized for the specific characteristics of the Vietnamese language. As a result, the system handles medical, technical, or business terminology effectively, minimizing recognition errors compared to general tools.

Key benefits of applying this workflow include:

• Saving post-meeting time: Employees only need to review the output rather than typing it from scratch.
• Increasing transparency: All decisions are clearly recorded, avoiding disputes about what was agreed upon.
• Easy retrieval: You can search for specific keywords in the minutes instead of listening to audio files.

Implementation Advice for Businesses

If you are looking to start automating this process, keep the following points in mind:

1. Audio Quality: No matter how good the AI is, poor-quality microphones will still cause difficulties for STT. Encourage the use of high-quality recording devices in meeting rooms.
2. Verify Critical Information: AI supports humans, but humans must still double-check important figures, dates, and names before sending the official minutes.
3. Integrate into Workflows: Connect the meeting minutes tool with project management software (like Jira, Trello, or Asana) to automatically create tasks from the extracted Action Items.

Conclusion

Combining Vietnamese STT and LLM summarization is a practical solution for enhancing team efficiency. Instead of spending hours on administrative tasks, your team can focus on executing the agreed-upon decisions.

With technology developed specifically for Vietnamese and flexible integration via API, AIVISION provides a comprehensive solution from speech recognition to content summarization. You can experience these features directly on the s2speech.com platform.

Start free to see the difference that AI technology brings to your workflow.

Frequently asked questions

Can Vietnamese STT handle interspersed English?

Yes. Modern STT technology, particularly models trained for the Vietnamese market like those from AIVISION, supports code-switching well, helping to accurately identify English terms appearing within Vietnamese sentences.

How long does it take to create AI meeting minutes?

The time depends on the length of the meeting. With streaming solutions, text is generated in near real-time. For recorded files, the processing is much faster than listening back, typically taking only a few minutes to complete the summary for a one-hour meeting.

Can I edit the minutes after the AI generates them?

Absolutely. AI minutes are a smart draft. You can edit, add to, or remove unnecessary parts before sharing them with other members to ensure absolute accuracy.

What is the cost of using the AI meeting minutes service?

Costs are typically calculated based on the amount of data processed (tokens) or audio duration.

How can I integrate this technology into my existing system?

You can use the REST or WebSocket APIs provided. AIVISION supports standard-compatible endpoints, making it easy for developers to integrate recording and summarization features into internal software or mobile applications.

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