Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Raeesy, Zeynab"'
Autor:
Richardson, Chris, Zhang, Yao, Gillespie, Kellen, Kar, Sudipta, Singh, Arshdeep, Raeesy, Zeynab, Khan, Omar Zia, Sethy, Abhinav
Personalization, the ability to tailor a system to individual users, is an essential factor in user experience with natural language processing (NLP) systems. With the emergence of Large Language Models (LLMs), a key question is how to leverage these
Externí odkaz:
http://arxiv.org/abs/2310.20081
Autor:
Richardson, Christopher, Kar, Sudipta, Kumar, Anjishnu, Ramachandran, Anand, Khan, Omar Zia, Raeesy, Zeynab, Sethy, Abhinav
Open domain conversational agents can answer a broad range of targeted queries. However, the sequential nature of interaction with these systems makes knowledge exploration a lengthy task which burdens the user with asking a chain of well phrased que
Externí odkaz:
http://arxiv.org/abs/2302.10978
Autor:
Hu, Hu, Yang, Xuesong, Raeesy, Zeynab, Guo, Jinxi, Keskin, Gokce, Arsikere, Harish, Rastrow, Ariya, Stolcke, Andreas, Maas, Roland
Accents mismatching is a critical problem for end-to-end ASR. This paper aims to address this problem by building an accent-robust RNN-T system with domain adversarial training (DAT). We unveil the magic behind DAT and provide, for the first time, a
Externí odkaz:
http://arxiv.org/abs/2012.07353
Autor:
Punjabi, Surabhi, Arsikere, Harish, Raeesy, Zeynab, Chandak, Chander, Bhave, Nikhil, Bansal, Ankish, Müller, Markus, Murillo, Sergio, Rastrow, Ariya, Garimella, Sri, Maas, Roland, Hans, Mat, Mouchtaris, Athanasios, Kunzmann, Siegfried
Multilingual ASR technology simplifies model training and deployment, but its accuracy is known to depend on the availability of language information at runtime. Since language identity is seldom known beforehand in real-world scenarios, it must be i
Externí odkaz:
http://arxiv.org/abs/2007.03900
Autor:
Chandak, Chander, Raeesy, Zeynab, Rastrow, Ariya, Liu, Yuzong, Huang, Xiangyang, Wang, Siyu, Joo, Dong Kwon, Maas, Roland
This paper presents our modeling and architecture approaches for building a highly accurate low-latency language identification system to support multilingual spoken queries for voice assistants. A common approach to solve multilingual speech recogni
Externí odkaz:
http://arxiv.org/abs/2006.00703
Autor:
Raeesy, Zeynab, Gillespie, Kellen, Yang, Zhenpei, Ma, Chengyuan, Drugman, Thomas, Gu, Jiacheng, Maas, Roland, Rastrow, Ariya, Hoffmeister, Björn
This article presents a whisper speech detector in the far-field domain. The proposed system consists of a long-short term memory (LSTM) neural network trained on log-filterbank energy (LFBE) acoustic features. This model is trained and evaluated on
Externí odkaz:
http://arxiv.org/abs/1809.07832
Publikováno v:
2013 IEEE 10th International Symposium on Biomedical Imaging; 2013, p1328-1331, 4p
Autor:
Raeesy, Zeynabalsadat
Magnetic resonance imaging (MRI) technology has facilitated capturing the dynamics of speech production at fine temporal and spatial resolutions, thus generating substantial quantities of images to be analysed. Manual processing of large MRI database
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635202