Speaker identification: Giving your media a voice of its own
Ever wish your audio and video content could tell you exactly who’s speaking, and when? Our DeepVA AI’s Speaker Identification model does just that, intelligently distinguishing between different voices and even recognizing specific speakers to bring clarity to your media assets.
identify speakers across your media assets
What does Speaker Identification do?
The Speaker Identification model analyses audio and video content to detect, distinguish and optionally recognise different speakers. It segments recordings based on voice changes and assigns consistent speaker IDs across the timeline—even without knowing who the speakers are.
For voices without labels, the system automatically distinguishes them, assigning a unique “Speaker 1,” “Speaker 2” ID throughout the content. This makes it easy to track different individuals across media files and add names later if needed. Furthermore, you can also build your own speaker datasets—how cool is that?
The benefits of choosing us
Automatic identification of speakers in audio and video
Automatically assign text to individual speakers in panel discussions, interviews, or protocols—for more readable transcripts and subtitles.
Scalable across media archives, broadcasts, and live streams
Our Speaker Identification module analyzes hours of content efficiently and without human supervision.
Adapt the AI to your needs
With the Deep Model Customizer, you can train individual speaker recognition models — perfect for identifying recurring individuals in your media,
Speaker Identification module is part of our Deep Media Analyzer application. Check it out now:
What you’ll get
Diarization (splitting content by speaker)
Our AI intelligently separates audio based on different voices, giving you segmented content for each speaker.
Speaker labeling
The system assigns consistent IDs like “Speaker 1,” “Speaker 2,” across your timeline, even if the speakers are initially unknown.
Timestamped speaker segments
Get exact start and end times for each speaker’s turn, ensuring precise tracking and easy referencing.
Optional integration with transcription workflows
Connects effortlessly with transcription tools to attribute spoken words to the correct speaker, enhancing accuracy.
Training of speaker-specific models
Beyond just distinguishing voices, you can train the system to recognize and name specific individuals for advanced identification.
Practical Applications
Putting speaker identification to work
frequently asked questions
Have a question? We’ve got answers
Does the model recognize who is speaking, or just separate voices?
By default, the model distinguishes between speakers without naming them. However, known speaker profiles can be trained for identification if desired.
Can it handle overlapping speech or noisy environments?
The model performs best with clean audio and clear speaker turns. Overlapping speech may reduce accuracy but is being continuously improved.
Is it compatible with transcription tools?
What kind of metadata is returned?
Is your service GDPR compliant?
Yes, DeepVA is fully GDPR compliant. We take data protection and privacy seriously and ensure that all personal data is processed in accordance with GDPR regulations.
How is my data handled? Does the AI learn from my data?
You have full control over your data on our AI platform, ensuring it remains secure and compliant. By default, we do not use your data to train our models, keeping it proprietary. However, you have the option to train models using your data, and in that case, it will remain exclusive to your organization.
What type of data do you store?
By default, we do not process your data beyond what is required to provide our services. If additional processing is necessary, it will only occur as outlined in your instructions or where legally required. For example, data may be transferred or processed as needed to fulfill service requirements, always in alignment with our agreements.
To learn more about how we process data and the safeguards in place, please refer to our Data Processing Agreement.
