Cross-lingual Information Retrieval with BERT
Table 4: MQWV scores on the Lithuanian analysis and development sets and Q1 queries.
['Approach', 'Analysis Set Text', 'Analysis Set Speech', 'Development Set Text', 'Development Set Speech']
We compare BERT models with other CLIR models in terms of MQWV scores. The first row in the table shows the best results of non-neural CLIR models, which are probabilistic CLIR model and probabilistic occurrence model. In this table, we separate the results based on the type of source documents: text or speech. The results of the BERT model on the speech sets are the best, compared with the non-neural CLIR systems, QRANN and Dot-product models, while the results on the text sets are comparable to those from the non-neural systems, and better than the other neural systems.