Multiple Discriminative DNNs for I-Vector Based Open-Set Language Recognition
نویسندگان
چکیده
منابع مشابه
Multiclass Discriminative Training of i-vector Language Recognition
The current state-of-the-art for acoustic language recognition is an i-vector classifier followed by a discriminatively-trained multiclass back-end. This paper presents a unified approach, where a Gaussian i-vector classifier is trained using Maximum Mutual Information (MMI) to directly optimize the multiclass calibration criterion, so that no separate back-end is needed. The system is extended...
متن کاملSet Based Discriminative Ranking for Recognition
Recently both face recognition and body-based person reidentification have been extended from single-image based scenarios to video-based or even more generally image-set based problems. Set-based recognition brings new research and application opportunities while at the same time raises great modeling and optimization challenges. How to make the best use of the available multiple samples for e...
متن کاملOut-of-Set i-Vector Selection for Open-set Language Identification
Current language identification (LID) systems are based on an ivector classifier followed by a multi-class recognition back-end. Identification accuracy degrades considerably when LID systems face open-set data. In this study, we propose an approach to the problem of out of set (OOS) data detection in the context of open-set language identification. In our approach, each unlabeled i-vector in t...
متن کاملDNN-based Discriminative Scoring for Speaker Recognition Based on i-vector
Correspondence: [email protected] Center for Speech and Language Technologies, Tsinghua University, ROOM 4-416, Information Sci & Tech Building, Tsinghua University, 100084 Beijing, China Full list of author information is available at the end of the article Abstract One of the state-of-the-art approaches to speaker recognition is based on factor analysis, especially the i-vector model. By...
متن کاملSpecialized Support Vector Machines for open-set recognition
Recently, the open-set recognition problem has received more attention by the machine learning community given that most classification problems in practice require an open-set treatment. Thus far, many classifiers were mostly developed for the closed-set scenario, i.e., the scenario of classification in which it is assumed that all test samples belong to one of the classes the classifier was t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of Korean Institute of Communications and Information Sciences
سال: 2016
ISSN: 1226-4717
DOI: 10.7840/kics.2016.41.8.958