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1
Stage-wise Fine-tuning for Graph-to-Text Generation ...
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HySPA: Hybrid Span Generation for Scalable Text-to-Graph Extraction ...
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3
InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection ...
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4
Learning Shared Semantic Space for Speech-to-Text Translation ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.195 Abstract: Having numerous potential applications and great impact, end-to-end speech translation (ST) has long been treated as an independent task, failing to fully draw strength from the rapid advances of its sibling - text machine translation (MT). With text and audio inputs represented differently, the modality gap has rendered MT data and its end-to-end models incompatible with their ST counterparts. In observation of this obstacle, we propose to bridge this representation gap with Chimera. By projecting audio and text features to a common semantic representation, Chimera unifies MT and ST tasks and boosts the performance on ST benchmarks, MuST-C and Augmented Librispeech, to a new stateof-the-art. Specifically, Chimera obtains 27.1 BLEU on MuST-C ENDE, improving the SOTA by a +1.9 BLEU margin. Further experimental analyses demonstrate that shared semantic space indeed conveys common knowledge between these two tasks and thus paves a new ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://dx.doi.org/10.48448/f8cw-bq75
https://underline.io/lecture/26286-learning-shared-semantic-space-for-speech-to-text-translation
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5
Joint Biomedical Entity and Relation Extraction with Knowledge-Enhanced Collective Inference ...
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6
Event-Centric Natural Language Processing ...
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7
VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension ...
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8
Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation ...
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