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Language Model Combination and Adaptation Using Weighted Finite State Transducers.
The combination module has the functions that include the 3D model combination and 1D relevance.
In this paper, we introduced an ensemble model combination and adaptation based ASR system with two characteristics: (1) large-scale combination of multiple ASR systems based on a Recognizer Output Voting Error Reduction (ROVER) system, and (2) multi-pass unsupervised speaker adaptation for deep neural network acoustic models and topic adaptation on language model.
Results obtained with first- and second-order CRF models alone (without model combination) and after post-processing are shown with differences compared to the corrected run.
For the model combination and refinement step of our pipeline, we used a novel global local model combination algorithm.
MULTICOM-REFINE, MUProt, and MULTICOM (our human-expert predictor) implemented the fourth and fifth portions of our general pipeline (model evaluation, model combination and refinement).
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For breaking random wave cases, the computed results of the two model combinations and FUNWAVE agreed well with the measurements.
Parallel model combination (PMC) and its recent advances are reviewed and a novel algorithm called PC-PMC is proposed.
A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling.
This further proves that our model combination algorithm can detect and combine structural segments with better qualities and refine the final model.
In the following, all model components summarized in the "Complete model: combination of reversible and irreversible dynamics" section are reduced to the weakly non-local case.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com