Model-Agnostic and Language-Agnostic Voice Pipeline Improvement for the Agriculture Domain
FarmerChat is Digital Green's AI-powered agricultural advisory assistant for smallholder farmers, who access it in their own language through text, voice, or photographs. Voice is a critical channel for this population, yet field-recorded speech is challenging for general-purpose automatic speech recognition (ASR) because recordings frequently contain machinery noise, background media, competing speakers, and domain-specific agricultural vocabulary. These conditions disproportionately affect crop, pest, chemical, and quantity terms that carry the meaning of a farmer's query. We present a modular, model-agnostic pipeline for improving ASR quality in FarmerChat without fine-tuning or replac...
| Authors | Aakash Singh, Lakshmi Pedapudi, Chandrashekar M S et al. |
|---|---|
| Primary category | eess.AS |
| Published | 17 September 2026 |
| Last updated at source | 17 September 2026 |
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- DigiGreen/agri-voice-evalDataset · cited by
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- DigiGreen/agri-voice-evalDataset
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