Enabling Multilingual Mode in AI Meetings: Combining Vietnamese-English STT and LLM

In international work environments, language barriers often disrupt the flow and precision of meetings. When participants alternate between Vietnamese and English—a practice known as code-switching—manual note-taking frequently leads to semantic errors. This article analyzes the technical workflow of combining Speech-to-Text (STT) technology with Large Language Models (LLM) to produce high-quality English meeting minutes, allowing your team to focus on content rather than linguistic hurdles.

The Challenge of Code-Switching

Many standard transcription systems struggle when speakers switch between Vietnamese and English within a single sentence. For example, a statement like "We need to review the frontend code immediately" may be misrecognized if the system is not specifically trained on the phonetic characteristics of Vietnamese mixed with English keywords.

For businesses with offices in Vietnam, the USA, or other markets, maintaining information accuracy is critical. Inaccurate meeting minutes can lead to flawed project decisions. Therefore, implementing specialized AI solutions for Vietnamese-English communication is a necessary step to enhance internal and partner communication efficiency.

Technical Workflow: From Speech to Standardized Text

To transform mixed-language meetings into professional documentation, the data processing workflow typically involves two main stages: raw speech recognition and natural language processing via LLM.

Stage 1: Speech-to-Text (STT) with Code-Switching Capability

The first step is converting speech to text. Here, the quality of the STT model is decisive. A robust system must:

• Accurately identify English keywords embedded in Vietnamese sentences.
• Provide word-level timestamps for easy traceability.
• Handle the specific phonetic nuances of native Vietnamese speakers pronouncing English words.

AIVISION provides Speech-to-Text services with a focus on Vietnamese, offering strong support for code-switching scenarios. Trained on real-world Vietnamese speech data, the system minimizes recognition errors when encountering technical or commercial English terms.

Stage 2: Processing and Translation with LLM

Raw text from STT often contains minor spelling errors, incomplete sentences, or random language mixing. This is where the Large Language Model (LLM) plays its role. The LLM performs the following tasks:

• Text Normalization: Correcting spelling, adding punctuation, and structuring sentences.
• Semantic Translation: Converting Vietnamese text into natural English while preserving context and professional tone.
• Summarization and Extraction: Identifying key points, action items, and responsible parties.

The final output is a clear, coherent English meeting minute, ready to be shared with international partners without the need for time-consuming manual editing.

Practical Benefits for Businesses

Automating this workflow delivers concrete value to management teams and staff:

• Faster Documentation: Instead of spending hours listening back and taking notes, minutes are generated almost immediately after the meeting ends.
• Consistency: The LLM maintains a professional and consistent tone in output documents, regardless of who is speaking.
• Reduced Errors: Eliminates mistakes caused by fatigue or lack of focus during manual note-taking.
• Improved Accessibility: Team members who did not attend the meeting can easily grasp the content through standardized English minutes.

Comparison: Manual vs. AI-Automized Workflow

Criteria	Manual Workflow	STT + LLM Workflow
Processing Time	Slow (depends on meeting length)	Fast (automated post-meeting)
Accuracy	Depends on the note-taker	High (AI-verified)
Code-Switching	Prone to omission or errors	Handles mixed keywords well
Multilingual Support	Requires bilingual staff	Automatic semantic conversion
Labor Cost	High	Low (requires only final review)

Deployment Recommendations

When selecting technology for multilingual meetings, businesses should consider the following factors:

1. Training Data Quality: The STT system should be trained on real-world Vietnamese speech data, including code-switching cases, to ensure high accuracy.
2. Integration Capabilities: The API should support common standards like REST or WebSocket for easy integration into existing online meeting platforms or project management software.
3. Data Security: Meeting data often contains sensitive information. Ensure the provider has clear security policies and complies with data regulations.
4. Flexibility: The system should allow customization of industry-specific keywords to optimize recognition results for specific fields.

AIVISION, with experience deploying speech AI for hundreds of enterprises in Vietnam and abroad, offers solutions tailored to these needs. Our system supports both real-time processing and file handling, providing flexibility across various use cases.

Conclusion

Combining STT and LLM is an inevitable direction to solve language challenges in multilingual meetings. Instead of worrying about manual transcription and translation, teams can leverage the power of Vietnamese-English AI to create accurate and professional English meeting minutes.

To experience this workflow, explore the services offered by AIVISION. Start with a free trial to evaluate speech recognition quality and code-switching handling capabilities in your specific work context.

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Frequently asked questions

What is code-switching in STT?

It is the ability of a speech recognition system to accurately process sentences that alternate between two languages, such as Vietnamese and English, within the same line or conversation segment.

How do I create English meeting minutes from Vietnamese speech?

You use STT to convert speech into raw text, then use an LLM to translate and normalize that text into English, ensuring semantic and grammatical accuracy.

Does AIVISION support languages other than Vietnamese and English?

Yes, AIVISION’s STT system supports 24 languages, including Spanish, Thai, Chinese, Japanese, and Korean, making it suitable for diverse translation applications.

Is my meeting data secure?

AIVISION is committed to customer data security. Businesses can refer to the detailed privacy policy on the website or contact the technical team directly for more information.

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