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Found 6 papers, 2 papers with code
Motion2Language, unsupervised learning of synchronized semantic motion segmentation
We find that both contributions to the attention mechanism and the encoder architecture additively improve the quality of generated text (BLEU and semantic equivalence), but also of synchronization.
Ranked #1 on
Motion Captioning
on KIT Motion-Language
Guided Attention for Interpretable Motion Captioning
While much effort has been invested in generating human motion from text, relatively few studies have been dedicated to the reverse direction, that is, generating text from motion.
Improving Patent Mining and Relevance Classification using Transformers
Patent analysis and mining are time-consuming and costly processes for companies, but nevertheless essential if they are willing to remain competitive.
A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect
This study presents a large scale benchmarking on cloud based Speech-To-Text systems: {Google Cloud Speech-To-Text}, {Microsoft Azure Cognitive Services}, {Amazon Transcribe}, {IBM Watson Speech to Text}.
Semantic Similarity from Natural Language and Ontology Analysis
Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments -- most of which demand high cognitive skills (e. g. learning or decision processes).
Semantic Measures for the Comparison of Units of Language, Concepts or Instances from Text and Knowledge Base Analysis
Semantic measures are widely used today to estimate the strength of the semantic relationship between elements of various types: units of language (e. g., words, sentences, documents), concepts or even instances semantically characterized (e. g., diseases, genes, geographical locations).
