Automating Multilingual Subtitles for International Conferences: Combining STT and LLM

In international conferences, language barriers often diminish the attendee experience and disrupt the flow of information. Implementing an automated subtitle system that combines Speech-to-Text (STT) and Large Language Models (LLMs) is a practical solution that ensures inclusivity and efficiency for all participants. This article analyzes the technical process and practical considerations for building a seamless, accurate AI translation system.

Challenges in Creating Subtitles for Multilingual Conferences

International conferences typically feature speakers from diverse cultural backgrounds using different languages. Traditional manual captioning faces significant limitations in speed and cost. Interpreters must process information in real time, leading to latency and a high risk of errors when speakers talk quickly or use specialized terminology.

For large-scale events, ensuring low latency and high accuracy is a prerequisite. A good subtitle system must do more than just convert speech to text; it must understand context to translate naturally. This is where the combination of STT and LLMs delivers high performance.

Technical Process: Combining STT and LLM

To produce high-quality automated subtitles, the system must process content through two main stages: speech recognition and natural language processing.

Stage 1: Speech-to-Text (STT)

The first step is converting audio into text. Modern STT technology must meet strict requirements:

• Handling code-switching: The ability to accurately recognize and transcribe when speakers alternate vocabulary or sentences in another language (e.g., Vietnamese and English) within the same utterance.
• Low latency: Support for streaming via WebSocket to update subtitles instantly, creating a real-time interactive feel.
• Accuracy: Crucial for medical, technical, or business fields where specialized terminology demands high precision.

AIVISION provides a Speech-to-Text solution with a strong focus on Vietnamese, effectively handling Vietnamese-English code-switching and supporting 24 different languages. Trained on a massive corpus of hundreds of thousands of hours of Vietnamese speech, the model achieves stable accuracy in real-world scenarios such as business meetings and conferences.

Stage 2: Processing and Translation with LLM

Raw text from STT often lacks punctuation, may contain typos, or lacks contextual clarity. Large Language Models (LLMs) play a key role at this stage:

• Text cleaning: Automatically adding punctuation, segmenting sentences, and standardizing formatting.
• Context understanding: LLMs analyze the entire dialogue to identify the topic, resulting in more accurate translation than word-for-word conversion.
• Multilingual translation: Converting content into the target language (English, Spanish, Thai, etc.) with a natural style that fits the reader's cultural context.

This combination transforms a mere string of characters into meaningful, understandable, and professional content.

Specific Benefits for Conference Organizers

Applying this technology brings practical value to international events:

1. Enhanced user experience: Attendees can follow the content as the speaker delivers it, without losing information due to language barriers.
2. Reduced staffing costs: Effectively supports or replaces interpreter teams, especially for long discussion sessions or less common language groups.
3. Content storage and reuse: All subtitles and translations can be stored for video editing, summary emails, or post-conference reference materials.

Practical Implementation Advice

For an automated subtitle system to operate effectively, organizers should consider the following:

• Check input audio quality: Microphone quality and the acoustic environment directly affect STT accuracy. Use lapel or table microphones with good noise reduction capabilities.
• Provide specialized dictionaries: If the conference involves many specific terms, provide a glossary to the system to improve the accuracy of both STT and LLM.
• Test before the event: Always run trials with realistic scenarios, including situations with multiple speakers or speakers with distinct accents.

AIVISION supports integrating STT and LLM APIs into your existing systems. With OpenAI-compatible API interfaces and streaming capabilities, deployment becomes flexible and rapid. You can explore more application solutions on our Blog to learn more about specific use cases.

Conclusion

Automating multilingual subtitles is no longer a distant solution but a new standard for professional international conferences. By combining the precision of STT with the contextual understanding of LLMs, organizers can eliminate language barriers, creating an inclusive and effective communication environment.

If you are looking for an automated subtitle solution for your upcoming event, start today. AIVISION provides high-accuracy tools with flexible customization options. Start free to experience the service and Contact us for advice on the solution that best fits your needs.

Frequently asked questions

How much latency do automated subtitles have compared to the speaker's voice?

Latency depends on the system's processing speed and network connection. With modern streaming solutions like AIVISION's, latency is typically very low, often just a few seconds, allowing viewers to follow the content seamlessly.

Can the system handle difficult specialized terminology?

Yes. By combining LLMs and providing a specialized glossary before the event, the system can accurately recognize and translate specific terms in fields such as medicine, engineering, or finance.

Do I still need to hire interpreters if I have automated subtitles?

Automated subtitles are a powerful support tool that reduces the pressure on interpreters. However, for critical sessions, combining both (subtitles + interpreters) is still recommended to ensure absolute accuracy and flexibility in communication.

Which languages does AIVISION support for translation?

AIVISION supports 24 different languages for translation applications, including popular languages such as Vietnamese, English, Spanish, Thai, Chinese, Japanese, and Korean, among others.

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