Smarter Voice Selection and Multi-Speaker Control in AI Dubbing

Enterprise video localization doesn’t just need speed. It needs polish, consistency, and control.

That’s why we’re introducing two major upgrades to AI dubbing inside Smartcat: a new AI Voice Recommendation System and enhanced Manual Multi-Speaker Support with advanced voice tuning. Together, these improvements make it easier to create high-quality, brand-aligned multilingual videos — without the guesswork or rework that traditionally slows teams down.

For teams looking to build the best workflow for creating multilingual subtitles and AI voiceovers at scale, these enhancements bring structure and precision to every step of the process.

Selecting the right AI voice used to involve scrolling through hundreds of options and relying on trial and error. Now, voice selection is structured, guided, and language-aware.

What’s changed with Smartcat’s Media Agent?

Inside the Subtitle Editor, the new AI Voice Recommendation System helps you quickly identify the best voices for your target language and use case. Voices are intelligently categorized to simplify decision-making.

You’ll see recommended voices created from the same native language as your selected target language, helping ensure more natural and authentic delivery. You’ll also see optimized voices — strong alternatives trained in other native languages but still well suited to your project.

To support consistency across markets, the system highlights which voices are already in use in other language versions of the same project. This makes it easier to maintain a unified style across multilingual releases.

Teams can also reuse recently applied voices within their workspace or rely on a curated Voice Library, where project managers and administrators can mark preferred voices to standardize output across teams.

Voices can be previewed directly within the Subtitle Editor, and users can toggle between original and AI-generated audio before finalizing. The result is faster selection, more predictable quality, and far less trial-and-error.

For enterprise teams localizing training programs, marketing campaigns, or internal communications, this means more professional, publish-ready videos delivered at scale — with voice quality that feels intentional, not experimental.

Many enterprise videos feature multiple speakers: hosts, trainers, interviewees, narrators layered over dialogue. Preserving that structure in localized versions is critical for clarity and credibility.

With Manual Multi-Speaker Support, teams can assign distinct AI voices to different speakers within the same project. Voice settings can be applied globally, per speaker, or even per individual segment. You can adjust voice speed, stability, and style to match pacing, tone, and delivery requirements — whether that’s an energetic product demo or a measured executive update.

This level of control is essential when building the best workflow for creating multilingual subtitles alongside AI dubbing, because subtitles, voice timing, and speaker identity must remain aligned across every language version.

Instead of flattening multi-speaker content into a single generic voice, structure, personality, and speaker identity remain intact across languages.

Quality assurance often requires iteration. A single line may need refinement — but regenerating an entire project shouldn’t be necessary.

With the new controls, you can regenerate individual segments at any time without affecting the rest of the timeline. Pauses and structure are preserved, so fine-tuning never disrupts synchronization. If you update a speaker’s voice, all segments assigned to that speaker automatically reflect the change. If you only need to improve one moment, you can regenerate that segment alone.

This balance of flexibility and control significantly reduces manual rework and supports a scalable, repeatable workflow for multilingual video production.

Together, the AI Voice Recommendation System and Manual Multi-Speaker Support give enterprise teams the best of both worlds: intelligent suggestions to accelerate production, and granular controls to meet brand, narrative, and quality standards.

If your team is scaling multilingual video content and refining the best workflow for creating multilingual subtitles and AI voiceovers, these upgrades are now available inside Smartcat.

Open the Subtitle Editor, select AI voiceover, and experience smarter voice selection and deeper speaker control in your next project.