Voices Releases Framework to Calibrate DNSMOS for Higher-Quality AI Speech Training Data
Summary
Voices releases a white paper outlining a four-step human-in-the-loop framework to calibrate DNSMOS audio-quality thresholds for specific AI speech uses, aiming to prevent usable training data from being discarded and avoid higher training time and costs.
Key Points
- Voices releases a white paper on calibrating DNSMOS to improve source-data quality for AI speech-model training.
- The guide presents a four-step human-in-the-loop framework for setting use-case-specific audio-quality thresholds.
- Voices says uncalibrated DNSMOS can exclude usable source data, increasing training time and costs.