Papers by Hamed Bonab
A Multi-Task Architecture on Relevance-based Neural Query Translation (P19-1)
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| Challenge: | Existing models for cross-lingual information retrieval are not aware of the vocabulary distribution of the retrieval corpus. |
| Approach: | They propose a multi-task learning approach to train a Neural Machine Translation model with a Relevance-based Auxiliary Task (RAT) for search query translation. |
| Outcome: | The proposed model achieves 16% improvement over a strong baseline on Italian-English query-document dataset. |
100,000 Podcasts: A Spoken English Document Corpus (2020.coling-main)
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Ann Clifton, Sravana Reddy, Yongze Yu, Aasish Pappu, Rezvaneh Rezapour, Hamed Bonab, Maria Eskevich, Gareth Jones, Jussi Karlgren, Ben Carterette, Rosie Jones
| Challenge: | Podcasts are a large and growing repository of spoken audio. |
| Approach: | They propose to use podcasts as a resource for speech processing and linguistics . they use a corpus of 100,000 podcasts to study the complexity of the domain . |
| Outcome: | The Spotify Podcast Dataset is the largest corpus of transcribed speech data . the dataset contains 60,000 hours of podcasts, with a range of genres and styles . |