As a strategic partner of ElevenLabs, Omtera helps businesses implement AI voice technologies through the right use cases. ElevenLabs AI Dubbing offers a faster, more scalable, and manageable localization approach compared to traditional dubbing processes for companies that want to adapt video and audio content into different languages.
One of the most important challenges faced by businesses seeking to expand into international markets is the time and cost required to reproduce existing content in different languages. Re-recording a training video, product presentation, webinar recording, or corporate communications video for every country requires many operational steps, including translation, studio work, voice actors, editing, and quality control.
ElevenLabs AI Dubbing automates a significant part of this process with artificial intelligence. The system analyzes speech in the source content, separates speakers from one another, translates the text into the target language, and creates a new voice recording that resembles the speaker’s original voice characteristics. According to ElevenLabs’ official documentation, its dubbing technology can process audio and video content in more than 90 languages while aiming to preserve speakers’ tone, timing, emotion, and distinctive voice characteristics.
ElevenLabs AI Dubbing is an AI-powered localization solution that creates a new audio layer by translating speech in a video or audio recording into another language.
The process is not limited to translating text from one language into another. A successful dubbing project requires the following elements to be managed together:
ElevenLabs separates source speech from the soundtrack and other audio components, allowing speech to be recreated in the target language. This approach is particularly important for interviews, podcasts, training content, and corporate videos featuring multiple speakers.
The ElevenLabs AI Dubbing process consists of several complementary stages, from uploading content to exporting the final output.
In the first stage, the user uploads the video or audio file they want to translate to the ElevenLabs platform. The content can be uploaded directly as a file or processed through a link from a supported online source.
ElevenLabs help documentation states that links from YouTube, TikTok, and other online video sources can be used. This means teams may not need to run a separate download and re-upload process for each piece of content.
For enterprise use, it is important to check audio quality before uploading the file to the system. Heavy background noise, people speaking over one another, or low-quality microphone recordings may affect transcription and speaker separation performance.
The system analyzes speech in the source content and converts it into written text using speech-to-text technology.
This stage forms the foundation of the entire dubbing process. An error in the source text may also affect the subsequent translation and voice generation stages. For this reason, technical terms, product names, personal names, industry jargon, and abbreviations should be reviewed carefully.
For example, if expressions such as “API,” “SaaS,” “CRM,” or a product name are detected incorrectly in a software company’s video, this may cause meaning and pronunciation problems in the target-language voiceover.
When multiple people speak in a video, ElevenLabs identifies different speakers through its speaker detection feature.
Each speaker has their own intonation, rhythm, emphasis, and vocal tone. Therefore, correctly separating speakers is critical for creating a consistent audio experience in the target language.
For example, in a webinar recording featuring three executives, each speaker needs to be identified separately. This allows the speakers to be heard with separate voices resembling their own original voice characteristics when the content is translated from English into French, rather than all being rendered with the same synthetic voice.
Once transcription is complete, the source text is translated into the selected target language. However, translation for dubbing differs from standard document translation.
A sentence that appears correct in written form may not fit within the available time window in the video when spoken aloud. In addition, the number of words and speaking time required to express the same meaning may vary between languages.
Introduced in May 2026, Dubbing v2 aims to adapt translation not only for semantic accuracy but also for spoken delivery and synchronization requirements. According to ElevenLabs, its sync-aware translation system helps align the beginning, ending, and speaking speed of sentences with the source content.
For example, a short marketing message in English may become longer when translated into Turkish. The system may restructure the translation into a more natural and concise expression so that it fits the timing of the video more effectively.
After the translation is completed, a new spoken audio track is generated in the target language. ElevenLabs aims to preserve the source speaker’s tone, rhythm, vocal color, and delivery style as much as possible.
Voice cloning technology analyzes characteristics such as a speaker’s timbre, accent, speaking pace, and pronunciation, enabling these characteristics to be used in newly generated speech. ElevenLabs offers different voice cloning approaches, including Instant Voice Cloning and Professional Voice Cloning.
This feature is particularly valuable for content creators, company executives, trainers, and media organizations that want to preserve their personal brand. A product announcement delivered by a CEO in English can be presented in French or Arabic with a voice character resembling the same person, rather than with a completely different voice.
When using voice cloning, speaker consent, usage rights, and internal corporate security policies must always be considered.
The newly generated audio needs to align with the scenes and speaking intervals in the video. ElevenLabs attempts to adjust the beginning and ending points of speech generated in the target language according to the source video.
This process is not exactly the same as visual lip-sync. The primary objective of the dubbing system is to adapt the rhythm, pauses, and total timing of the speech to the video. For highly precise broadcast, cinema, or advertising projects, additional production tools or human review may be required for final editing and lip-sync.
With ElevenLabs Productions, transcription, translation, voice matching, and synchronization processes can be carried out with the contribution of professional language and production specialists alongside AI models.
Once automatic dubbing is complete, the content can be reviewed through Dubbing Studio. Users can review the text, translations, speakers, and audio segments and make the necessary edits.
Dubbing Studio supports exporting AAC, MP3, and WAV audio files, as well as audio tracks as ZIP files, timeline data in AAF format, subtitles in SRT format, and speaker, timing, transcription, and translation information in CSV format.
These output options make it easier for enterprise teams to connect ElevenLabs to their existing video editing and localization processes.
Dubbing Studio is designed for teams that want detailed control over a project instead of directly using a fully automatically generated output.
Users can review the source transcription and the translation in the target language. Misidentified words, industry-specific terms, or expressions that do not match the brand language can be corrected manually.
For example, the term “customer journey” can be translated according to the terminology used by the organization rather than using a generic translation.
Speech can be managed in separate segments. This allows teams to regenerate only problematic sections without having to recreate the entire file from the beginning.
This feature provides operational efficiency, especially for long webinars, training videos, and podcast episodes.
The voice used for each speaker can be controlled separately. Depending on the organization’s usage permissions and project requirements, a voice resembling the source speaker, a custom corporate voice, or an appropriate voice from the ElevenLabs Voice Library can be selected.
A pronunciation dictionary can be created for brand names, personal names, technical terms, and abbreviations. ElevenLabs states that dictionaries in TXT or PLS format can be used within Dubbing Studio.
For example, the pronunciation of Omtera, ElevenLabs, SaaS, or an industry-specific product name in the target language can be defined in advance. This makes it possible to achieve a more consistent pronunciation standard across different videos.
Marketing teams can localize a single product video with ElevenLabs AI Dubbing instead of recording it again for different countries.
For example, a SaaS product video created in Türkiye can be converted into English, French, and Arabic versions. Instead of translating only the words, currencies, date formats, calls to action, and example scenarios can also be adapted to local expectations in each market.
Providing training videos in only one language within international teams can negatively affect employee experience and knowledge transfer.
Human resources and operations teams can translate onboarding, information security, product training, occupational health and safety, or company policy videos into the languages preferred by employees.
In this scenario, project managers can determine which videos should be prioritized, department managers can review content accuracy, and IT teams can manage access, file security, and integration processes.
A webinar conducted by a company in English does not have to remain limited to participants who speak English.
The webinar recording can be translated into different languages with ElevenLabs and published on YouTube, a training portal, or a corporate content center. This makes it possible to achieve broader international reach from a single event.
Help center videos explaining how to use a product can be translated into different languages. Users can listen to product instructions in their own language without having to read subtitles.
For example, a software company can localize videos such as “creating an account,” “setting up an integration,” and “preparing a report” according to its target markets.
Podcasts, interviews, documentaries, and YouTube content can be adapted into different languages. ElevenLabs customer examples show that content creators have built international channels by preserving the voice identities of the same characters across different languages.
In a traditional dubbing process, translators, voice actors, studio teams, and audio engineers work together. While this approach can offer a high level of creative control, it may require significant time, coordination, and budget for a large number of languages and pieces of content.
ElevenLabs AI Dubbing combines steps such as transcription, translation, speaker detection, and voice generation within the same workflow.
AI dubbing is particularly advantageous in the following situations:
However, human review should not be completely removed from content that is legally, culturally, or strategically critical to the brand. Even when an automatic translation appears correct, it should also be evaluated in terms of local meaning, humor, cultural sensitivity, and industry terminology.
ElevenLabs offers API endpoints for creating and managing dubbing projects through an API. Businesses can send video or audio files from their applications to ElevenLabs, monitor the status of the dubbing project, and retrieve the completed output as MP3 or MP4.
This feature is particularly important for companies with large content archives.
For example, when a new training video is published on an e-learning platform, the system can automatically:
Such a structure can reduce manual file transfers and make localization operations more scalable.
Using ElevenLabs technology alone is not enough to establish a successful enterprise localization process. Content selection, target-language strategy, terminology, voice permissions, quality control, and publishing processes must be designed together.
First, existing video and audio content should be listed. Content should be prioritized according to usage frequency, relevance, target market, and commercial importance.
Instead of translating every piece of content into all available languages, priority languages should be selected based on the customer base, growth objectives, and content demand.
A centralized glossary should be created for product names, technical terms, personal names, and frequently used corporate expressions.
The necessary permissions must be obtained to reproduce a person’s voice with artificial intelligence or recreate it in other languages. The duration of use, channels, and countries should be clearly defined.
People who speak the target language at a native level should review the translation, pronunciation, consistency of meaning, and cultural suitability.
Metrics such as watch time, completion rate, engagement, conversion, and support requests for localized content should be monitored. This makes it possible to understand which languages and content types generate the highest value.
Omtera helps businesses position ElevenLabs not only as a one-time content production tool but also as a measurable and sustainable AI audio infrastructure.
Omtera’s approach within the scope of ElevenLabs may include the following areas:
Omtera’s ElevenLabs service approach includes AI audio use case development, technical integration, workflow design, security, and enterprise-scale adoption initiatives.
For example, for an organization with hundreds of training videos, simply “translating the videos” is not enough. It is necessary to determine which videos should be translated first, which languages should be prioritized, who will approve translations, how version changes will be tracked, and on which platforms the outputs will be published.
Omtera can support the design of this operational model in alignment with ElevenLabs features.
Applying the following controls in AI dubbing projects can improve output quality:
ElevenLabs Dubbing costs may vary depending on factors such as content duration, number of target languages, selected workflow, and voice generation. The platform may show the relevant cost to the user before the project is approved. Since pricing and credit conditions may change over time, current information should be checked at the beginning of the project.
ElevenLabs AI Dubbing is a comprehensive AI voice solution that aims to preserve the speaker’s voice characteristics and expressive delivery while adapting video, training, webinar, podcast, and corporate communications content into different languages. However, successful results require more than automatic translation; content prioritization, terminology management, voice permissions, quality control, system integration, and performance measurement must be planned together.
As ElevenLabs’ strategic partner, Omtera can help businesses transform AI Dubbing technology into a secure, scalable structure aligned with enterprise objectives.
Are you ready to scale your multilingual content production with ElevenLabs? Schedule a short meeting with Omtera and create your AI Dubbing roadmap today.
What is ElevenLabs AI Dubbing?
ElevenLabs AI Dubbing is an AI-powered localization solution designed to preserve speakers’ voice characteristics, intonation, emotion, and speaking timing while translating video and audio content into different languages.
How many languages does ElevenLabs AI Dubbing support?
According to ElevenLabs’ current official documentation, the dubbing feature supports audio and video localization in more than 90 languages. Since language coverage and features may be updated over time, the official documentation should be reviewed before starting a project.
Can ElevenLabs preserve the speaker’s original voice?
ElevenLabs aims to preserve the speaker’s timbre, pace, tone, and delivery characteristics in the target language as much as possible. The success of the output depends on source audio quality, language, speaking style, and project settings.
Does ElevenLabs AI Dubbing provide lip synchronization?
ElevenLabs Dubbing primarily focuses on adapting the beginning, ending, and pace of speech to the source video. Projects requiring detailed visual lip synchronization at cinema or advertising quality may require additional video production tools and manual editing.
Is it possible to translate one video into multiple languages?
Yes. Multiple target languages can be added to the same Dubbing Studio project. For multilingual projects, ElevenLabs recommends creating the project with one language first and then adding the remaining languages within the project so that edits can be synchronized more easily between languages.
Can ElevenLabs AI Dubbing be used through an API?
Yes. The ElevenLabs API can be used to create a dubbing project, monitor its processing status, and retrieve completed audio or video outputs programmatically.
Does AI dubbing completely replace human translators?
AI dubbing can automate many technical and operational steps. However, for content that is critical from a brand, legal, cultural, or high-visibility perspective, it is recommended that translation and audio outputs be reviewed by specialists.
Can ElevenLabs AI Dubbing be used for enterprise training?
Yes. Onboarding, product training, compliance, information security, and operations videos can be translated into the languages preferred by employees. This makes it possible to create a more accessible and consistent training experience across international teams.
How is ElevenLabs AI Dubbing pricing calculated?
The cost may vary depending on content duration, number of target languages, the dubbing method used, and additional processes such as voice generation. The current cost should be viewed within the platform after the project settings are completed.
What services can Omtera provide for ElevenLabs AI Dubbing projects?
Omtera can provide enterprise support in areas such as use case development, target-language and content prioritization, Dubbing Studio workflow design, API integration, terminology management, governance, pilot implementation, training, and performance measurement.
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