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Table 5 Comparison of word accuracies (percent) between the HMM baseline and the template-based methods

From: Integrated exemplar-based template matching and statistical modeling for continuous speech recognition

Speakers (no. of words) Dr. 1 (3,248) Dr. 2 (5,085) Dr. 3 (3,988) Dr. 4 (2,759) Dr. 5 (6,421) Average
Baselines 72.14 82.50 84.00 74.20 79.32 78.43
All templates (LLR) 73.53 84.22 85.98 75.74 80.67 80.03
MLTS (KL) 73.22 83.39 84.87 75.35 80.15 79.40
Template compression (KL) 73.55 83.61 85.21 75.71 80.39 79.70
  1. Word accuracies (%) for HMM baselines, LLR-based all templates, and KL-based MLTS and template compression for five doctors in the telehealth task.