| 書目名稱 | Robust Speech Recognition of Uncertain or Missing Data |
| 副標題 | Theory and Applicati |
| 編輯 | Dorothea Kolossa,Reinhold H?b-Umbach |
| 視頻video | http://file.papertrans.cn/832/831364/831364.mp4 |
| 概述 | Scientists and researchers in the field of speech recognition will find an overview of the state of the art in robust speech recognition..Professionals working in speech recognition will find strategi |
| 圖書封面 |  |
| 描述 | .Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition..The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding |
| 出版日期 | Book 2011 |
| 關鍵詞 | Audiovisual speech recognition; Deconvolution; Missing feature theory; Noise robustness; Packet loss; Sou |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-21317-5 |
| isbn_softcover | 978-3-642-43868-4 |
| isbn_ebook | 978-3-642-21317-5 |
| copyright | Springer-Verlag Berlin Heidelberg 2011 |
|Archiver|手機版|小黑屋|
派博傳思國際
( 京公網(wǎng)安備110108008328)
GMT+8, 2026-1-25 10:40
發(fā)表于 2025-3-21 17:33:45
