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Found 16 papers, 5 papers with code
On the Importance of Signer Overlap for Sign Language Detection
We quantify this with a detailed analysis of the effect of signer overlap on current sign detection benchmark data sets.
Clean Text and Full-Body Transformer: Microsoft's Submission to the WMT22 Shared Task on Sign Language Translation
The BLEU score is further improved to 1. 08 on the dev set by applying features extracted from a lip reading model.
Dialectal Speech Recognition and Translation of Swiss German Speech to Standard German Text: Microsoft's Submission to SwissText 2021
This paper describes the winning approach in the Shared Task 3 at SwissText 2021 on Swiss German Speech to Standard German Text, a public competition on dialect recognition and translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Multi-channel Transformers for Multi-articulatory Sign Language Translation
Sign languages use multiple asynchronous information channels (articulators), not just the hands but also the face and body, which computational approaches often ignore.
Quantitative Survey of the State of the Art in Sign Language Recognition
This work presents a meta study covering around 300 published sign language recognition papers with over 400 experimental results.
Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation
We report state-of-the-art sign language recognition and translation results achieved by our Sign Language Transformers.
Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective
Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture.
Cultural Vocal Bursts Intensity Prediction
Sign Language Recognition
+1
MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language
Sign language recognition is a challenging and often underestimated problem comprising multi-modal articulators (handshape, orientation, movement, upper body and face) that integrate asynchronously on multiple streams.
Neural Sign Language Translation
SLR seeks to recognize a sequence of continuous signs but neglects the underlying rich grammatical and linguistic structures of sign language that differ from spoken language.
SubUNets: End-To-End Hand Shape and Continuous Sign Language Recognition
We propose a novel deep learning approach to solve simultaneous alignment and recognition problems (referred to as "Sequence-to-sequence" learning).
Ranked #15 on
Sign Language Recognition
on RWTH-PHOENIX-Weather 2014
Re-Sign: Re-Aligned End-To-End Sequence Modelling With Deep Recurrent CNN-HMMs
This work presents an iterative re-alignment approach applicable to visual sequence labelling tasks such as gesture recognition, activity recognition and continuous sign language recognition.
Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled
Furthermore, we demonstrate its use in continuous sign language recognition on two publicly available large sign language data sets, where it outperforms the current state-of-the-art by a large margin.
Sign Spotting using Hierarchical Sequential Patterns with Temporal Intervals
This paper tackles the problem of spotting a set of signs occuring in videos with sequences of signs.
Extensions of the Sign Language Recognition and Translation Corpus RWTH-PHOENIX-Weather
This paper introduces the RWTH-PHOENIX-Weather 2014, a video-based, large vocabulary, German sign language corpus which has been extended over the last two years, tripling the size of the original corpus.
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus
This paper introduces the RWTH-PHOENIX-Weather corpus, a video-based, large vocabulary corpus of German Sign Language suitable for statistical sign language recognition and translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
