TY - GEN
T1 - Generating of sign system for Bahasa Indonesia (SIBI) root word gestures using deep temporal sigmoid belief network
AU - Darmana, Surya A.
AU - Rakun, Erdefi
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/4/19
Y1 - 2019/4/19
N2 - Sign language is a language that uses a combination of hand gestures and lip movements for people with hearing impairment to communicate. In Indonesia there are two sign language systems used, Sign System for Indonesian Language known as SIBI (Sistem Isyarat Bahasa Indonesia) recognizes as the official sign language system by the Indonesian Government. This research is focused on the generation process of skeleton sequence; in which represent a SIBI hand gesture excluding the finger joints. The hand skeleton that will be generated from the generation process is limited to root-word gestures only. Some researchers were using a Restricted Boltzmann Machine model and its variant known as Deep Belief Networks (DBN) to solve the sequence modelling problems. One of DBN variants is Sigmoid Belief Network (SBN). An SBN is a Bayesian network that models a binary visible vector. Deep Temporal Sigmoid Belief Network (DTSBN) is a sequence of SBNs (with deep architecture) arranged in such way that at any given time step has a fully generative process capability, where data are readily generated from the model using ancestral sampling. Since, DTSBN performance is quite novel for this particular case, we decided to implement the DTSBN model using the SIBI dataset from the previous research to construct generated hand-skeleton gestures which represent SIBI’s root-word gestures. Based on the success of the experimental DTSBN model that has been successfully generated new skeleton sequences, which represent a SIBI hand gesture. Some of the inputs to the model include cartesian coordinates from shoulder joints, elbow joints, and wrist joints and the newly generated data are proven have no significant difference with the actual data set.
AB - Sign language is a language that uses a combination of hand gestures and lip movements for people with hearing impairment to communicate. In Indonesia there are two sign language systems used, Sign System for Indonesian Language known as SIBI (Sistem Isyarat Bahasa Indonesia) recognizes as the official sign language system by the Indonesian Government. This research is focused on the generation process of skeleton sequence; in which represent a SIBI hand gesture excluding the finger joints. The hand skeleton that will be generated from the generation process is limited to root-word gestures only. Some researchers were using a Restricted Boltzmann Machine model and its variant known as Deep Belief Networks (DBN) to solve the sequence modelling problems. One of DBN variants is Sigmoid Belief Network (SBN). An SBN is a Bayesian network that models a binary visible vector. Deep Temporal Sigmoid Belief Network (DTSBN) is a sequence of SBNs (with deep architecture) arranged in such way that at any given time step has a fully generative process capability, where data are readily generated from the model using ancestral sampling. Since, DTSBN performance is quite novel for this particular case, we decided to implement the DTSBN model using the SIBI dataset from the previous research to construct generated hand-skeleton gestures which represent SIBI’s root-word gestures. Based on the success of the experimental DTSBN model that has been successfully generated new skeleton sequences, which represent a SIBI hand gesture. Some of the inputs to the model include cartesian coordinates from shoulder joints, elbow joints, and wrist joints and the newly generated data are proven have no significant difference with the actual data set.
KW - Deep temporal sigmoid belief network
KW - DTSBN
KW - Sequence generation
KW - Sign system for Indonesian language
UR - http://www.scopus.com/inward/record.url?scp=85071133404&partnerID=8YFLogxK
U2 - 10.1145/3330482.3330494
DO - 10.1145/3330482.3330494
M3 - Conference contribution
AN - SCOPUS:85071133404
T3 - ACM International Conference Proceeding Series
SP - 221
EP - 225
BT - ICCAI 2019 - 2019 5th International Conference on Computing and Artificial Intelligence
PB - Association for Computing Machinery
T2 - 5th International Conference on Computing and Artificial Intelligence, ICCAI 2019
Y2 - 19 April 2019 through 22 April 2019
ER -