Search Results for author:
Found 3 papers, 0 papers with code
Initial Decoding with Minimally Augmented Language Model for Improved Lattice Rescoring in Low Resource ASR
Our approach is applicable for training speech recognition systems under low resource conditions where speech data and compute resources are insufficient, while there is a large text corpus that is available in the target language.
A Hierarchical Approach to Conditional Random Fields for System Anomaly Detection
Furthermore, hierarchical solutions can adapt well to changes at a localized level, learning on new data and changing environments when parts of a system are over-hauled, and translate these learnings to a global view of the system over time.
Flavour Enhanced Food Recommendation
We propose a mechanism to use the features of flavour to enhance the quality of food recommendations.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
