Question about NEMO Diarization Clustering
Hello NVIDIA Developer Community,
I hope this message finds you well. I am currently working on a project involving NVIDIA’s NEMO toolkit, specifically the diarization functionality, and I have a question regarding the clustering of speakers.
Context
In my current setup, NEMO’s diarization module effectively distinguishes between different speakers in an audio stream, labeling them as “Speaker 0”, “Speaker 1”, and so on. While this is quite helpful, I am interested in taking this a step further.
Question
Is it possible to train NEMO to recognize and label specific voices with personalized labels, such as actual names? For instance, instead of generic labels like “Speaker 0”, could NEMO label a speaker as “Elliot Fieldhouse-Allen” if it recognizes my voice?
Objective
The goal is to enhance the diarization output by making it more intuitive and user-friendly, particularly for applications where knowing the specific speaker’s identity is crucial.
Additional Information
- Current Setup: I am using the latest version of NEMO with the default diarization settings.
- Technical Proficiency: I have a solid understanding of AI and ML models and am comfortable with custom training pipelines if necessary.
Request for Guidance
I would appreciate any insights or guidance on the following:
- Feasibility: Is this customization feasible with NEMO’s current capabilities?
- Implementation: What steps or resources would be required to achieve this functionality?
- Examples: If anyone has implemented a similar solution, could you please share your experience or relevant code snippets?
Thank you in advance for your time and assistance. I am looking forward to any recommendations or advice from the community.
Best regards,
Elliot Fieldhouse-Allen