Integrating Google Cloud Speech-to-Text with Real-time Language Translation

Question

I'm working on a project that involves real-time language translation using Google Cloud services. I've successfully implemented Google Cloud Speech-to-Text for transcribing spoken words, and I'm now looking to integrate real-time language translation into the pipeline.

I've explored Google Cloud Translation API for language translation, but I'm struggling to find a seamless way to translate the transcribed text as it's being generated by Speech-to-Text in real-time. Ideally, I want the translation to occur on the fly, providing the translated text almost instantaneously.

Has anyone tackled a similar scenario or has suggestions on how to achieve real-time language translation using Google Cloud services? Any code snippets or architectural guidance would be greatly appreciated. Thanks!

Answer 1

According to the Google Cloud documentation, to translate an audio file or stream of speech into text of another language you can consider using a combination of the Cloud Speech-to-Text and Cloud Translation API. In this, you can use speech to text api to convert audio into text and then we can use translation API to convert text into the targeted language.

Google recommends setting the sampling rate to 16000 Hz to achieve the best result or setting it to the speaker’s voice frequency. The stream will divide the speech into frames and send them to the Request. The size of frames will affect the latency and the larger the frames, the greater the latency. Google recommends setting the frame size to 100 milliseconds.

Before diving into any conclusion my recommendation is to once you're able to transcribe audio from streaming input, measure the time of response of the API and then add Translation API with the text generated. By this, you can find the latency issue.

You can also take a look at this documentation to know more about the implementation and code.