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In addition, Section 4.5 describes our proposed system combination approach that combines discriminatively trained complementary systems.
In this work, several word- and subword-based systems were combined with the system combination approach presented in [91].
System combination improved performance; in almost all cases, the combined system outperformed the best performing single system.
We then combined the decoded transcripts using ROVER, a recognition system combination software available from NIST.
They used a unique technique called a dual system combination to construct various (>10) complementary acoustic models and combined their outputs using ROVER, which contributed to about 7 % RWERR.
SGMM+DNN: system combination of MMI-SGMM and DNN-HMM.
Mitra et al. [103] focused on system combination from word lattices.
Seigel et al. [102] employed a system combination approach based on word and grapheme ASR.
Our proposed method to specifically provide desired complementary systems for system combination further improved performance.
The results are based on a system combination of MMI-SGMM and DNN.
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We tested five types of system combinations, as shown in Table 8.
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