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When compared with a conventional word-based RNNLM (W), the best proposed hybrid RNNLM, H-R2, obtained 2.41 % relative PER reduction and 1.54 % relative WER reduction on average.
The best proposed hybrid RNNLM (H-R2), reported in Section 5.3, is compared against the conventional word-based RNNLM (W).
In terms of recognition performance, the best proposed hybrid RNNLM, a reduced-hybrid which uses a mixed input sequence of words and PMs, obtained 1.54 % relative WER reduction when compared with a conventional word-based RNNLM as hybrid input types provide more flexible unit choices for LM re-scoring.
Particle Swarm Optimization (PSO) algorithm is one of the best proposed heuristic optimization algorithms in Artificial Intelligence applied to many engineering problem.
All results are expressed as mean±S.E.M. Student's t-test was used to confirm the differences between the best proposed approach and the other groups.
Thus, Case-2 is selected as best proposed design.
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Article IX, proposed decree; Article X, decree entered.
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