Use case
Audio transcription
Unlock the power of complex audio transcription for next-gen AI initiatives
Why Labelbox for audio transcription
Increase data quality
Generate high-quality data by combining advanced tooling, humans, AI and on-demand services in a unified solution.
Accelerate time to value
Rapidly integrate data, create quality training data, and deploy models to production.
Access on-demand expertise
Highly-skilled labeling services, data science support, and industry insights available on-demand
Collaborate in real-time
Enjoy direct access to internal and external labelers with real-time feedback on labels and quality via Labelbox platform.
Capturing rich audio details for advanced AI projects
Tackle complex audio transcription tasks utilizing LLMs and the Labelbox Platform. Simplify the process of capturing key audio details, from spoken words and intonations to background noise and non-verbal cues.
Streamlining your audio labeling workflows with customizations
Define custom transcription instructions and punctuation to ensure the data perfectly aligns with your specific use case. Embrace the user-friendly Audio Editor to simplify tasks while our global talent pool of skilled Aligners accelerate the creation of high-quality data tailored to your needs.
Accelerating development with on-demand services
Access an on-demand, highly skilled data labeling service with subject matter expertise to match your use cases. Collaborate with the workforce in real-time to maintain high data quality while keeping human labeling costs to a minimum using AI and automation techniques.
Customer spotlight
Dialpad, a leading AI-powered customer intelligence platform company used fine-tuning to build a powerful LLM over five years via five billion minutes of business conversations. The model offers out of the box capabilities to businesses to accurately summarize business calls, extract important insights and offer in-the-moment coaching to sellers and customer reps. Advanced discovery, curation, and annotation capabilities were crucial for building high-quality training datasets. Human evaluation was also critical to ensure quality outcomes before the system was turned live. Labelbox enabled this organization to accelerate the creation of the LLM by 75% through rich, integrated capabilities for data preparation and human evaluation.
