arXiv:1811.00347
공식 코드 · Papers with Code
How2: A Large-scale Dataset for Multimodal Language Understanding
원문 초록
In this paper, we introduce How2, a multimodal collection of instructional videos with English subtitles and crowdsourced Portuguese translations. We also present integrated sequence-to-sequence baselines for machine translation, automatic speech recognition, spoken language translation, and multimodal summarization. By making available data and code for several multimodal natural language tasks, we hope to stimulate more research on these and similar challenges, to obtain a deeper understanding of multimodality in language processing.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
KIT's Low-resource Speech Translation Systems for IWSLT2025: System Enhancement with Synthetic Data and Model Regularization
TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS
BeaverTalk: Oregon State University's IWSLT 2025 Simultaneous Speech Translation System
From Tens of Hours to Tens of Thousands: Scaling Back-Translation for Speech Recognition
HENT-SRT: Hierarchical Efficient Neural Transducer with Self-Distillation for Joint Speech Recognition and Translation
Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with Aphasia
토론
이 논문과 연결된 포럼 글이 아직 없습니다.