Fingerspelling detection and recognition – Our dataset reflects an increased usage of fingerspelling in interpretations of STEM documents. Identifying instances of fingerspelling and mapping these instances onto the corresponding English words can help researchers better understand signing patterns. We provide...
Fingerspelling detection and recognition – Our dataset reflects an increased usage of fingerspelling in interpretations of STEM documents. Identifying instances of fingerspelling and mapping these instances onto the corresponding English words can help researchers better understand signing patterns. We provide...
We used a variable signed input dataset to train a VR-based ASL recognition system. Rather than placing constraints on signers, we encouraged them to spontaneously produce the sign they use for the English word equivalent (e.g., produce the ASL sign MILK for the English word “milk”), rep...
The CNN is trained for classification of 100 words on Boston ASL (Lexicon Video Dataset) LVD dataset with more than 3300 English words signed by 6 different signers. 70% of the dataset is used for Training while the remaining 30% dataset is used for testing the model. The proposed work ...
Otherwise, it needs to be computed from sensor data. A useful open source tool for computing IMU parameters using Allan Deviation isori-drs/allan_variance_roswhich seems to be actively maintained. We recommend using this tool directly on ~15-24 hour dataset recording of the IMU being ...
We conducted a comparison of subjective frequency estimates from ASL-LEX and another independent dataset that used the same 1–7 rating scale for ASL signs, although the ratings were from deaf ASL signers residing in Canada (Mayberry et al., 2014). We verified that a total of 297 items shar...
Due to the relatively low sequencing depth and limited coverage of single-cell RNA-seq data, the probabilities of many AS events cannot be reliably estimated for all the single cells in a dataset. Therefore, the AS probability matrix greatly suffers from frequent missing values (marked as NA)....
applications. For example, because this dataset highlights the frequent use of fingerspelling for technical concepts, which inhibits DHH students{'} ability to learn,we develop models to identify fingerspelled words{---}which can later be used to query for appropriate ASL signs to suggest to ...
in Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison WLASL is a large video dataset for Word-Level American Sign Language (ASL) recognition, which features 2,000 common different words in ASL. Source: https://github.com/dxli94/WLASL ...
It contains some series of body gestures, which enables a person to interact without the need of spoken words. Although the use of sign language is very popular among the deaf mute people but the other communities don't even try to learn it, this creates a gulf of communication and hence...