From Zero to Global: A Complete AI Video Workflow Using Google Cloud & Gemini

Source: Dev.to

Content is king, but context is queen. In a country as diverse as Nigeria, creating digital content is only half the battle. The real challenge and opportunity lies in making that content accessible to everyone, whether they speak Yoruba, Hausa, or Igbo.

I recently explored the power of Google Vertex AI Studio to create a short film. I used cutting‑edge tools like Google Veo and Imagen (via the “Nano Banana” MCP server) to generate stunning visuals. But I didn’t want to stop at just great visuals—I wanted to ensure the message could resonate across Nigeria’s linguistic landscape.

Vertex AI Studio

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The Visual Foundation

First, the video itself was created using Vertex AI Studio. By leveraging generative video models like Veo, I was able to turn text prompts into high‑quality video clips. This formed the visual base of the project.

Creating visuals and films in Google Flow

To take this video from a silent clip to a localized story, I needed a suite of Google Cloud APIs. Below is the architecture for localization.

Prompting in Vertex AI Studio

Step 1 – Transcription (The Ear)

Tool: Google Cloud Speech‑to‑Text API

If your source video already has English audio (or any other language), the first step is extraction—you cannot translate what you haven’t captured.

The Speech‑to‑Text API listens to the audio track of the video and converts spoken words into a text transcript. It’s highly accurate and serves as the foundation for the rest of the pipeline.

Step 2 – Translation (The Brain)

Tool: Google Cloud Translation API

Once I had the raw text, the next step was bridging the cultural gap. I used the Translation API to convert the English transcript into Nigeria’s major languages: Yoruba, Hausa, and Igbo.

Google has been actively expanding support for African languages, meaning the translations are becoming increasingly nuanced—handling idioms and context better than ever before.

Step 3 – Vocalization (The Voice)

Tool: Google Cloud Text‑to‑Speech API

Reading subtitles is great, but hearing a message in your mother tongue is powerful. Using the Text‑to‑Speech API, I converted the translated Yoruba, Hausa, and Igbo scripts back into audio. This service synthesizes lifelike, neural speech—providing a natural, engaging voice‑over that can be synced back to the original video.

Step 4 – Subtitling (The Eyes)

Tool: Google Cloud Transcoder API

For accessibility (and for those watching on mute), subtitles are non‑negotiable.

Using the same translated text from Step 2, the Transcoder API lets you:

• Burn captions directly into the video file, or
• Generate side‑car files (e.g., .srt).

This ensures that even if the audio isn’t played, the message remains readable in the user’s local language.

Why This Matters for African Tech

While Vertex AI handles the heavy lifting of creative generation (building the world, the characters, and the movement), these specialized APIs are the bridge to the user.

For independent media houses, creators, and developers in Africa, this stack represents a massive opportunity. We can now build:

• Educational content that scales to every region.
• News broadcasts that automatically generate local versions.
• Entertainment that feels home‑grown, regardless of where it was produced.

The tools are there – it’s up to us to build the pipelines.

Did you find this workflow helpful? Follow me for more insights on building with Google Cloud and Vertex AI.

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