3 citations · 3 across the 1 of their papers we have counts for
14 papers
On the Difficulty of Segmenting Words with Attention
Ramon Sanabria, Hao Tang, Sharon Goldwater
Word segmentation, the problem of finding word boundaries in speech, is of interest for a range of tasks. Previous papers have suggested that for sequence-to-sequence models traine…
Talk, Don't Write: A Study of Direct Speech-Based Image Retrieval
Ramon Sanabria, Austin Waters, Jason Baldridge
Speech-based image retrieval has been studied as a proxy for joint representation learning, usually without emphasis on retrieval itself. As such, it is unclear how well speech-bas…
Multimodal Speech Recognition with Unstructured Audio Masking
Tejas Srinivasan, Ramon Sanabria, Florian Metze +1
Visual context has been shown to be useful for automatic speech recognition (ASR) systems when the speech signal is noisy or corrupted. Previous work, however, has only demonstrate…
Fine-Grained Grounding for Multimodal Speech Recognition
Tejas Srinivasan, Ramon Sanabria, Florian Metze +1
Multimodal automatic speech recognition systems integrate information from images to improve speech recognition quality, by grounding the speech in the visual context. While visual…
Looking Enhances Listening: Recovering Missing Speech Using Images
Tejas Srinivasan, Ramon Sanabria, Florian Metze
Speech is understood better by using visual context; for this reason, there have been many attempts to use images to adapt automatic speech recognition (ASR) systems. Current work,…
Multitask Learning For Different Subword Segmentations In Neural Machine Translation
Tejas Srinivasan, Ramon Sanabria, Florian Metze
In Neural Machine Translation (NMT) the usage of subwords and characters as source and target units offers a simple and flexible solution for translation of rare and unseen words.…