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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 28 1 Face Biometric Spoof Detection Method Using a Remote Photoplethysmography Signal Seung-Hyun Kim; Su-Min Jeon; Eui Chul Lee In: Sensors; Volume 22; Issue 8; Pages: 3070 (2022) BASE Show details 2 Automatic Classification Framework of Tongue Feature Based on Convolutional Neural Networks Jiawei Li; Zhidong Zhang; Xiaolong Zhu; Yunlong Zhao; Yuhang Ma; Junbin Zang; Bo Li; Xiyuan Cao; Chenyang Xue In: Micromachines; Volume 13; Issue 4; Pages: 501 (2022) BASE Show details 3 Bangla Sign Language (BdSL) Alphabets and Numerals Classification Using a Deep Learning Model Kanchon Kanti Podder; Muhammad E. H. Chowdhury; Anas M. Tahir; Zaid Bin Mahbub; Amith Khandakar; Md Shafayet Hossain; Muhammad Abdul Kadir In: Sensors; Volume 22; Issue 2; Pages: 574 (2022) BASE Show details 4 TASE: Task-Aware Speech Enhancement for Wake-Up Word Detection in Voice Assistants Guillermo Cámbara; Fernando López; David Bonet; Pablo Gómez; Carlos Segura; Mireia Farrús; Jordi Luque In: Applied Sciences; Volume 12; Issue 4; Pages: 1974 (2022) Abstract: Wake-up word spotting in noisy environments is a critical task for an excellent user experience with voice assistants. Unwanted activation of the device is often due to the presence of noises coming from background conversations, TVs, or other domestic appliances. In this work, we propose the use of a speech enhancement convolutional autoencoder, coupled with on-device keyword spotting, aimed at improving the trigger word detection in noisy environments. The end-to-end system learns by optimizing a linear combination of losses: a reconstruction-based loss, both at the log-mel spectrogram and at the waveform level, as well as a specific task loss that accounts for the cross-entropy error reported along the keyword spotting detection. We experiment with several neural network classifiers and report that deeply coupling the speech enhancement together with a wake-up word detector, e.g., by jointly training them, significantly improves the performance in the noisiest conditions. Additionally, we introduce a new publicly available speech database recorded for the Telefónica’s voice assistant, Aura. The OK Aura Wake-up Word Dataset incorporates rich metadata, such as speaker demographics or room conditions, and comprises hard negative examples that were studiously selected to present different levels of phonetic similarity with respect to the trigger words “OK Aura”. Keyword: convolutional neural network; deep learning; keyword spotting; speech enhancement; wake-up word URL: https://doi.org/10.3390/app12041974 BASE Hide details 5 Comparing Encoder-Decoder Architectures for Neural Machine Translation: A Challenge Set Approach ... Doan, Coraline. - : Université d'Ottawa / University of Ottawa, 2021 BASE Show details 6 Keyword Detection Based on RetinaNet and Transfer Learning for Personal Information Protection in Document Images Guo-Shiang Lin; Jia-Cheng Tu; Jen-Yung Lin In: Applied Sciences ; Volume 11 ; Issue 20 (2021) BASE Show details 7 Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges Sang Hoon Kim; Yun Jeong Lim In: Diagnostics ; Volume 11 ; Issue 9 (2021) BASE Show details 8 A New Deep Learning-Based Methodology for Video Deepfake Detection Using XGBoost Aya Ismail; Marwa Elpeltagy; Mervat S. Zaki... In: Sensors ; Volume 21 ; Issue 16 (2021) BASE Show details 9 Deep Learning Based Air-Writing Recognition with the Choice of Proper Interpolation Technique Fuad Al Abir; Md. Al Siam; Abu Sayeed; Md. Al Mehedi Hasan; Jungpil Shin In: Sensors; Volume 21; Issue 24; Pages: 8407 (2021) BASE Show details 10 Cardiovascular Disease Recognition Based on Heartbeat Segmentation and Selection Process Mehrez Boulares; Reem Alotaibi; Amal AlMansour... In: International Journal of Environmental Research and Public Health ; Volume 18 ; Issue 20 (2021) BASE Show details 11 Robust 3D Face Reconstruction Using One/Two Facial Images Ola Lium; Yong Bin Kwon; Antonios Danelakis... In: Journal of Imaging ; Volume 7 ; Issue 9 (2021) BASE Show details 12 Dynamic gesture classification of American Sign Language using deep learning Vaghasiya, Devina. - : Laurentian University of Sudbury, 2021 BASE Show details 13 Comparing Encoder-Decoder Architectures for Neural Machine Translation: A Challenge Set Approach Doan, Coraline. - : Université d'Ottawa / University of Ottawa, 2021 BASE Show details 14 СПОСОБ ПОЛУЧЕНИЯ ИНФОРМАЦИИ ОБ ОБЪЕКТЕ НА ОСНОВЕ АНАЛИЗА ЕГО ИЗОБРАЖЕНИЙ ... : THE CHOICE OF THE METHOD OF OBTAINING INFORMATION ABOUT THE OBJECT BASED ON THE ANALYSIS OF ITS IMAGES ... Локтев, Даниил Алексеевич; Локтев, Алексей Алексеевич. - : Институт проблем управления им. В. А. Трапезникова РАН, 2020 BASE Show details 15 A Deep Neural Network-Based Model for Named Entity Recognition for Hindi Language Sharma, Richa; Agarwal, Basant; Khan, Mohammad S.... In: ETSU Faculty Works (2020) BASE Show details 16 Automatic Language Identification Using Speech Rhythm Features for Multi-Lingual Speech Recognition Hwamin Kim; Jeong-Sik Park In: Applied Sciences ; Volume 10 ; Issue 7 (2020) BASE Show details 17 An Improved Approach for Text Sentiment Classification Based on a Deep Neural Network via a Sentiment Attention Mechanism Li; Liu; Zhang In: Future Internet ; Volume 11 ; Issue 4 (2019) BASE Show details 18 Tooth-Marked Tongue Recognition Using Gradient-Weighted Class Activation Maps Yue Sun; Songmin Dai; Jide Li... In: Future Internet ; Volume 11 ; Issue 2 (2019) BASE Show details 19 An Optimized Abstractive Text Summarization Model Using Peephole Convolutional LSTM Rahman; Siddiqui In: Symmetry ; Volume 11 ; Issue 10 (2019) BASE Show details 20 Identification Technology of Grid Monitoring Alarm Event Based on Natural Language Processing and Deep Learning in China Bai; Sun; Zang... In: Energies ; Volume 12 ; Issue 17 (2019) BASE Show details Page: 1 2

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