Real Time Translator AI-Enhanced Features (Powered by Azure AI and Azure OpenAI)

Boost Translation Feature for Subtitle Display
Immediate transcription and translation during conversations

Translations appear instantly even before the conversation segment finishes, eliminating delays.
Enables smooth communication among multilingual participants.

Utilize AI-powered transcription correction to automatically fix typos and errors, ensuring accurate translation.

The Transcription Proofreading Feature is designed to correct transcription errors—including typos, omissions, and grammatical mistakes—in speech-to-text output.
Once corrected, the transcripts can be translated to deliver more accurate and reliable multilingual communication.

Note:
1.Secondary use of the data is not performed.
2.The correction feature is applied after the speech content is confirm.
3.Currently, this feature supports Japanese and English.

Automatic Language Detection in Multilingual Meetings, prevent transcription and translation errors to ensure smooth meeting progression.

In multilingual meetings where three or more languages are spoken, it is often necessary to manually switch the input language based on the speaker. This can frequently lead to transcription or translation confusion.
The Automatic Language Detection feature detects the speaker’s language in real time and switches languages accordingly, enabling seamless communication.

See how this feature is applied in real-world scenarios.
■　Real-Time Voice Translation with Automatic Language Detection for Face-to-Face meetings
■　Smooth Multilingual Meetings for 3+ Languages – With Automatic Language Detection

AI automatically creates summaries from transcribed translation data, reducing the time needed for creating meeting minutes and reports.

With "Real Time Translator", you can automatically generate meeting minutes from transcribed and translated data using AI. The content is summarized by the entire meeting or by individual speakers, making it easy to review meetings and share information within your organization smoothly.

Note: Conversation history information used for summarization is not used for secondary purposes such as deep learning.