Audio Processing
How Our Technology Works
Transforming audio content into structured, real-time intelligence, delivering alerts, trend analyses and BI-ready datasets.
eMM audio processing is designed to help you identify what was said and who said it, fast and
at scale. Processing audio data in eMM consists of four components: audio segmentation, speech
recognition, speaker recognition and speaker clustering.
Our proprietary technology enables us to validate research directly on live streams, improving quality and reliability in real conditions.
Audio Segmentation
- Meaningful Context: We break continuous broadcast audio into meaningful sections to ensure accurate downstream analysis.
- Enhanced Precision: By isolating relevant audio, we reduce background noise and improve the precision of every subsequent recognition step.
Speech recognition
- Searchable Content: Converts spoken content into text to power search, profiles, alerts, and analysis across a wide range of broadcasts.
- Efficient Discovery: Enables faster discovery of mentions and topics without the need for manual listening.
Speaker Recognition & Speaker Clustering
- Meaningful Context: We break continuous broadcast audio into meaningful sections to ensure accurate downstream analysis.
- Enhanced Precision: By isolating relevant audio, we reduce background noise and improve the precision of every subsequent recognition step.
Do you want to see audio processing in action?
Book a demo
Tell us your target markets, key channels and specific use cases, whether you are focused on monitoring, deep analytics, or spokesperson tracking. We will demonstrate how eMM audio processing engine can be tailored to support your unique workflow.
Find more information about the other technologies used by eMM: