Results 11 to 20 of about 14,332 (195)
Brain-Inspired Polymer Dendrite Networks for Morphology-Dependent Computing Hardware. [PDF]
Adv Sci (Weinh)Although process variability is often perceived as a drawback in electronics, this work harnesses the stochastic nature of electropolymerization as a powerful ally for computation. The resulting conductive polymer dendrites exhibit unique structure‐property relationships and support in memory computing, paving the way for the development of a new class
Scholaert C +3 more
europepmc +2 more sources
On the Proper Treatment of Dynamics in Cognitive Science
Topics in Cognitive Science, EarlyView., 2023 Abstract This essay examines the relevance of dynamical ideas for cognitive science. On its own, the mere mathematical idea of a dynamical system is too weak to serve as a scientific theory of anything, and dynamical approaches within cognitive science are too rich and varied to be subsumed under a single “dynamical hypothesis.” Instead, after first ...
Randall D. Beer
wiley +1 more source
Information, 2021 Out-of-vocabulary (OOV) words are the most challenging problem in automatic speech recognition (ASR), especially for morphologically rich languages.
Eshete Derb Emiru +4 more
doaj +1 more source
Modeling Intra-label Dynamics and Analyzing the Role of Blank in Connectionist Temporal Classification [PDF]
Computer and Knowledge Engineering, 2018 The goal of many tasks in the realm of sequence processing is to map a sequence of input data to a sequence of output labels. Long short-term memory (LSTM), a type of recurrent neural network (RNN), equipped with connectionist temporal classification ...
Ashkan Sadeghi Lotfabadi +2 more
doaj +1 more source
Advancing Connectionist Temporal Classification with Attention Modeling [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 Accepted at ICASSP ...
Das, Amit +3 more
openaire +2 more sources
Fast offline transformer-based end-to-end automatic speech recognition for real-world applications
ETRI Journal, 2022 With the recent advances in technology, automatic speech recognition (ASR) has been widely used in real-world applications. The efficiency of converting large amounts of speech into text accurately with limited resources has become more vital than ever ...
Yoo Rhee Oh, Kiyoung Park, Kiyoung Park
doaj +1 more source
Sensors, 2020 Advanced automatic pronunciation error detection (APED) algorithms are usually based on state-of-the-art automatic speech recognition (ASR) techniques. With the development of deep learning technology, end-to-end ASR technology has gradually matured and ...
Long Zhang +7 more
doaj +1 more source
IEEE Access, 2021 Offline handwritten Chinese text recognition is one of the most challenging tasks in that it involves various writing styles, complex character-touching, and large number of character categories.
Yintong Wang +3 more
doaj +1 more source
Recognition of English speech – using a deep learning algorithm
Journal of Intelligent Systems, 2023 The accurate recognition of speech is beneficial to the fields of machine translation and intelligent human–computer interaction. After briefly introducing speech recognition algorithms, this study proposed to recognize speech with a recurrent neural ...
Wang Shuyan
doaj +1 more source
American Sign Language Alphabet Recognition Using Inertial Motion Capture System with Deep Learning
Inventions, 2022 Sign language is designed as a natural communication method for the deaf community to convey messages and connect with society. In American sign language, twenty-six special sign gestures from the alphabet are used for the fingerspelling of proper words.
Yutong Gu +5 more
doaj +1 more source