AGENTIC-SYSTEMSMarch 20, 20261 min read12 views

ProKWS: Personalized Keyword Spotting via Collaborative Learning of Phonemes and Prosody

Researchers have introduced ProKWS, a novel framework that enhances keyword spotting accuracy by integrating phonemic features with personalized prosody. This solution addresses word confusion and improves adaptability across diverse acoustic environments.

Electrical Engineering and Systems Science > Audio and Speech Processing

Title:ProKWS: Personalized Keyword Spotting via Collaborative Learning of Phonemes and Prosody

View PDF HTML (experimental)Abstract:Current keyword spotting systems primarily use phoneme-level matching to distinguish confusable words but ignore user-specific pronunciation traits like prosody (intonation, stress, rhythm). This paper presents ProKWS, a novel framework integrating fine-grained phoneme learning with personalized prosody modeling. We design a dual-stream encoder where one stream derives robust phonemic representations through contrastive learning, while the other extracts speaker-specific prosodic patterns. A collaborative fusion module dynamically combines phonemic and prosodic information, enhancing adaptability across acoustic environments. Experiments show ProKWS delivers highly competitive performance, comparable to state-of-the-art models on standard benchmarks and demonstrates strong robustness for personalized keywords with tone and intent variations.

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Source: arXiv cs.AI Recent

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