Results 21 to 30 of about 212,585 (307)
A Comparative Study on Transformer vs RNN in Speech Applications [PDF]
Automatic Speech Recognition & Understanding, 2019 Sequence-to-sequence models have been widely used in end-to-end speech processing, for example, automatic speech recognition (ASR), speech translation (ST), and text-to-speech (TTS).
Shigeki Karita +12 more
semanticscholar +1 more source
Pruned RNN-T for fast, memory-efficient ASR training [PDF]
Interspeech, 2022 The RNN-Transducer (RNN-T) framework for speech recognition has been growing in popularity, particularly for deployed real-time ASR systems, because it combines high accuracy with naturally streaming recognition. One of the drawbacks of RNN-T is that its
Fangjun Kuang +6 more
semanticscholar +1 more source
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations [PDF]
AAAI Conference on Artificial Intelligence, 2018 Emotion detection in conversations is a necessary step for a number of applications, including opinion mining over chat history, social media threads, debates, argumentation mining, understanding consumer feedback in live conversations, and so on ...
Navonil Majumder +5 more
semanticscholar +1 more source
Successive Image Generation from a Single Sentence [PDF]
ITM Web of Conferences, 2021 Through various examples in history such as the early man’s carving on caves, dependence on diagrammatic representations, the immense popularity of comic books we have seen that vision has a higher reach in communication than written words. In this paper,
Parab Amogh +4 more
doaj +1 more source
A multi-stage recurrent neural network better describes decision-related activity in dorsal premotor cortex [PDF]
, 2019 We studied how a network of recurrently connected artificial units solve a visual perceptual decision-making task. The goal of this task is to discriminate the dominant color of a central static checkerboard and report the decision with an arm ...
Chandrasekaran, Chandramouli +2 more
core +1 more source
Surgical phase recognition by learning phase transitions
Current Directions in Biomedical Engineering, 2020 Automatic recognition of surgical phases is an important component for developing an intra-operative context-aware system. Prior work in this area focuses on recognizing short-term tool usage patterns within surgical phases.
Sahu Manish +3 more
doaj +1 more source
Improved Recurrent Neural Network based BP Decoding Algorithm for Polar Codes
Guangtongxin yanjiu, 2022 In recent years, the emerging Deep Learning (DL) technology has made progress in the field of decoding. Current polar code neural network decoder has faster convergence speed and better Bit Error Rate (BER) performance than Belief Propagation (BP ...
Xue-lu DENG, Da-qin PENG
doaj +1 more source
Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topology [PDF]
, 2010 Background In many protein-protein interaction (PPI) networks, densely connected hub proteins are more likely to be essential proteins. This is referred to as the "centrality-lethality rule", which indicates that the topological placement of a protein in
Leong, Hon Wai +4 more
core +5 more sources
A CNN-RNN Framework for Crop Yield Prediction [PDF]
Frontiers in Plant Science, 2019 Crop yield prediction is extremely challenging due to its dependence on multiple factors such as crop genotype, environmental factors, management practices, and their interactions.
Saeed Khaki, Lizhi Wang, S. Archontoulis
semanticscholar +1 more source
Efficient processing of GRU based on word embedding for text classification
JOIV: International Journal on Informatics Visualization, 2019 Text classification has become very serious problem for big organization to manage the large amount of online data and has been extensively applied in the tasks of Natural Language Processing (NLP).
Muhammad Zulqarnain +3 more
doaj +1 more source