Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Sanabria, Ramon"'
Autor:
Gomez, Frank Palma, Sanabria, Ramon, Sung, Yun-hsuan, Cer, Daniel, Dalmia, Siddharth, Abrego, Gustavo Hernandez
Large language models (LLMs) are trained on text-only data that go far beyond the languages with paired speech and text data. At the same time, Dual Encoder (DE) based retrieval systems project queries and documents into the same embedding space and
Externí odkaz:
http://arxiv.org/abs/2404.01616
The efficacy of self-supervised speech models has been validated, yet the optimal utilization of their representations remains challenging across diverse tasks. In this study, we delve into Acoustic Word Embeddings (AWEs), a fixed-length feature deri
Externí odkaz:
http://arxiv.org/abs/2402.02617
Acoustic word embeddings are typically created by training a pooling function using pairs of word-like units. For unsupervised systems, these are mined using k-nearest neighbor (KNN) search, which is slow. Recently, mean-pooled representations from a
Externí odkaz:
http://arxiv.org/abs/2306.02153
Autor:
Sanabria, Ramon, Bogoychev, Nikolay, Markl, Nina, Carmantini, Andrea, Klejch, Ondrej, Bell, Peter
English is the most widely spoken language in the world, used daily by millions of people as a first or second language in many different contexts. As a result, there are many varieties of English. Although the great many advances in English automati
Externí odkaz:
http://arxiv.org/abs/2303.18110
Given the strong results of self-supervised models on various tasks, there have been surprisingly few studies exploring self-supervised representations for acoustic word embeddings (AWE), fixed-dimensional vectors representing variable-length spoken
Externí odkaz:
http://arxiv.org/abs/2210.16043
Human speech data comprises a rich set of domain factors such as accent, syntactic and semantic variety, or acoustic environment. Previous work explores the effect of domain mismatch in automatic speech recognition between pre-training and fine-tunin
Externí odkaz:
http://arxiv.org/abs/2203.00648
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 trained on tasks such as speech translation or speech recognition, attention
Externí odkaz:
http://arxiv.org/abs/2109.10107
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-based retrieval can work in practice -- both in an absolute sense and ver
Externí odkaz:
http://arxiv.org/abs/2104.01894
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 demonstrated the utility of visual context in an unrealistic setting, where a fix
Externí odkaz:
http://arxiv.org/abs/2010.08642
Multimodal automatic speech recognition systems integrate information from images to improve speech recognition quality, by grounding the speech in the visual context. While visual signals have been shown to be useful for recovering entities that hav
Externí odkaz:
http://arxiv.org/abs/2010.02384