I’m interested in integrating real-time AI-powered transcription and translation for multilingual Zoom meetings. What are the best practices for implementing this using Zoom APIs? How can I optimize latency while maintaining high accuracy, especially in large-scale meetings? I’d love insights on API combinations or external tools that work well for this, along with any potential challenges in scaling this solution for corporate or educational environments
best regards
shehzad khan
Hi Shahzad,
You can utilize the Meeting SDK to capture the raw audio. This raw audio stream can then be directed to a translation service or team for processing.
Then to deliver the translated text or audio to the end users, you could do it via websockets.
FYI though latency is always going to be a challenge.
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Hi Shazad,
There are a few different options for building a scalable transcription and translation service for multilingual meetings:
1. Zoom Meeting SDK
You can use the Windows or Linux Meeting SDK to access raw meeting data. You’ll be able to receive and process the raw audio stream in real time this way. Here’s an example Github repo that demonstrates how to access raw video and audio through the Linux Meeting SDK.
Many third-party transcription providers support streaming speech to text, so once you have the raw audio, you can stream it to the provider to receive real-time transcription.
2. Recall.ai
Another alternative is to use Recall.ai instead. It’s a simple 3rd party API that lets you use meeting bots to get raw audio/video from meetings and generate real-time transcripts in just a few lines of code. This will avoid the challenges associated with scaling your infrastructure to handle multiple large-scale meetings.
Integrating real-time AI-powered transcription and translation for multilingual Zoom meetings is a powerful feature, especially for corporate or educational settings. To implement this using Zoom APIs, you can leverage Zoom’s live transcription service in combination with external AI tools like Google Cloud Speech-to-Text or AWS Transcribe for more advanced capabilities and translation. The key to optimizing latency while maintaining accuracy lies in balancing server-side processing speed with AI model performance. For large-scale meetings, consider breaking down the audio streams into smaller, manageable segments to reduce delays and ensure scalability. Using WebSockets for real-time updates and asynchronous processing can help optimize the performance. You may face challenges with latency and bandwidth, so testing and adjusting your API requests in relation to meeting size is crucial. Additionally, ensure that your solution complies with data privacy regulations in different regions, as this can be a hurdle when scaling globally. Best regards, Luna Harper.