Combining STT and LLM for Automatic Multilingual Meeting Note Transcription

In modern business environments, manually taking notes during long meetings is inefficient and prone to missing critical details. To address this, the trend of automating meetings by integrating Speech-to-Text (STT) and Large Language Model (LLM) technology is becoming a new standard. This article analyzes how to build an intelligent AI voice note system, with a specific focus on handling multilingual content and optimizing the experience for Vietnamese users.

The Challenge of Note-Taking in Multilingual Meetings

Meetings in Southeast Asia or within multinational companies often take place in mixed-language environments. Participants may switch between Vietnamese and English when mentioning technical terms, brand names, or specific processes. If you rely solely on standard recording tools, editors must spend hours listening back and transcribing, leading to delays in decision-making.

Furthermore, understanding context in multilingual meetings is a significant challenge. An English sentence inserted into a Vietnamese conversation may carry specific technical meaning that simple translation tools often miss without conversational context. Therefore, the solution requires an STT platform capable of handling code-switching (language switching) smoothly and an LLM smart enough to interpret the content.

Architecture Combining STT and LLM

To build an effective AI voice note system, we need to combine two main technology layers:

1. The Audio Processing Layer (STT)

The role of this layer is to convert raw audio signals into accurate text, accompanied by timing information (timestamps). For Vietnamese meetings, STT accuracy is a critical factor.

AIVISION, with experience deploying speech AI for hundreds of enterprises in Vietnam and abroad, provides STT technology designed specifically for Vietnamese. A standout feature is its ability to handle Vietnamese mixed with English naturally. Instead of stopping or mispronouncing English words, the system recognizes them as part of the conversation flow.

2. The Semantic Processing Layer (LLM)

Raw text from STT is often verbose, repetitive, and filled with filler words. The task of the LLM is to "clean" and "upgrade" this content. The LLM performs the following tasks:

• Summarizing content: Condensing long conversations into key points.
• Reformatting: Converting free-form text into action items, decisions, and notes.
• Translating and interpreting: If the meeting involves foreign languages, the LLM can translate important segments into the group's common language or explain complex terminology.

Practical Workflow: From Audio to Complete Minutes

Here is a 4-step process to automate note-taking, ensuring accuracy and efficiency:

1. Real-time Audio Capture and Streaming: Use a WebSocket API to stream audio from a recording device or online meeting application. Real-time processing reduces latency and allows the system to start processing as soon as a speaker finishes a sentence.
2. STT Conversion with Timestamps: The STT system receives the audio and returns text with timestamps for each word. This is crucial for users to search for specific conversation segments later without having to listen to the entire audio file again.
3. LLM Processing: The text is divided into reasonable chunks and sent to the LLM. The prompt is designed to require the LLM to extract:

• The speaker (if identifiable).
• The main content of each section.
• Commitments or tasks to be done.

4. Publishing Minutes: The final result is pre-formatted (Markdown or Word) and stored in the system. Users can search, edit, and share it immediately.

Why a Vietnamese-Specific LLM is Needed

Many composite systems use general multilingual LLMs. However, Vietnamese communication culture and sentence structure have unique characteristics. An LLM optimized for Vietnamese will better understand:

• Forms of address and levels of formality.

• Common governance and business terms in Vietnam.

• Natural expression, avoiding a "mechanical" feel when translating from other languages to Vietnamese.

  The combination of Vietnamese-specific STT and this LLM creates a complete ecosystem, helping AI voice note systems achieve high accuracy and practical applicability.

Implementation Advice

If you are starting to build a meeting automation system, keep the following points in mind:

• Focus on Audio Quality: No matter how powerful the AI is, noisy or distorted input audio will significantly reduce STT accuracy. Encourage users to use quality microphones or dedicated recording devices.
• Personalize Prompts: Customize instructions for the LLM based on the industry. For example, a meeting in the healthcare sector will require different technical terms than one in construction.
• Human Review: AI is a support tool, not a complete replacement for human insight. Always take time to quickly review the minutes before sharing them widely.

Comparison: Manual vs. Automated Solutions

Criteria	Manual Note-Taking	STT + LLM Automation
Processing Time	Hours after the meeting	Near-instant
Coverage	Prone to omissions due to fatigue	Captures all content
Search	Difficult, requires re-reading	Search by keyword, time
Multilingual	Depends on editor's skills	Automatic code-switching handling
Operational Cost	High (personnel)	Optimized (usage-based)

Conclusion

Combining STT and LLM is no longer a distant concept but has become an essential tool for enhancing work efficiency. With the ability to handle multilingual content and optimize for Vietnamese, specialized solutions help businesses save time and ensure no important information is missed.

Instead of spending time listening to long audio files, you can focus on making decisions based on clear, structured minutes. This is the essence of modern meeting automation.

If you want to experience this workflow, consider the applications on the s2speech platform, such as AI Voice Note, where you can record, transcribe, and ask questions about note content directly.

Additionally, every account enjoys a daily free usage limit, enabling you to test the service without financial risk.

Contact the AIVISION team if you need advice on a deployment solution tailored to your business scale. We are always ready to support you in building smarter workflows.

Frequently asked questions

Can AI voice notes handle Vietnamese mixed with English?

Yes, specialized STT systems like AIVISION's are designed to handle code-switching between Vietnamese and English naturally, ensuring high accuracy in technical or business meetings.

Do I need to install complex software to use it?

Not necessarily. With applications like AI Voice Note on s2speech, you only need to use the mobile or web app to record, and the system will process it automatically. For developers, there are easy-to-integrate REST and WebSocket APIs.

How is meeting data security ensured?

AIVISION adheres to strict data security standards. Your data is encrypted and used only to provide the service to you; it is not used to retrain models for other customers.

What is the cost of using the AI voice note service?

Additionally, there is a daily free usage limit for every account for you to try out.

How is a Vietnamese LLM different from a general multilingual LLM?

An LLM optimized for Vietnamese has a deeper understanding of grammar, communication culture, and specific professional terms in Vietnam, resulting in translations and summaries that are more natural, accurate, and contextually appropriate than general models.

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