Name
Abstract | ||
|---|---|---|
In this research work, we develop a state-of-art model for identifying sentiment in Hindi-English code-mixed language. We introduce new phonemic sub-word units for Hindi-English code-mixed text along with a hierarchical deep learning model which uses these sub-word units for predicting sentiment. The results indicate that the model yields a significant increase in accuracy as compared to other models. |
Year | Venue | Field |
|---|---|---|
2018 | THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | Consonant vowel,Computer science,Speech recognition,Artificial intelligence,Machine learning |
DocType | Citations | PageRank |
Conference | 1 | 0.37 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Upendra Kumar | 1 | 4 | 4.84 |
| Vishal Veer Singh | 2 | 6 | 3.95 |
| Chris Andrew Gadde | 3 | 1 | 0.70 |
| Santhoshini Reddy | 4 | 1 | 0.70 |
| Amitava Das | 5 | 198 | 42.49 |