NDLI: Aligned-Parallel-Corpora Based Semi-Supervised Learning for Arabic Mention Detection

Content Provider	ACM Digital Library
Author	Zitouni, Imed Benajiba, Yassine
Abstract	In the last two decades, significant effort has been put into annotating linguistic resources in several languages. Despite this valiant effort, there are still many languages left that have only small amounts of such resources. The goal of this article is to present and investigate a method of propagating information (specifically mentions) from a resource-rich language such as English into a relatively less-resource language such as Arabic. We compare also this approach to its equivalent counterpart using monolingual resources. Part of the investigation is to quantify the contribution of propagating information in different conditions - based on the availability of resources in the target language. Experiments on the language pair Arabic-English show that one can achieve relatively decent performance by propagating information from a language with richer resources such as English into Arabic alone (no resources or models in the source language Arabic). Furthermore, results show that propagated features from English do help improve the Arabic system performance even when used in conjunction with all feature types built from the source language. Experiments also show that using propagated features in conjunction with lexically-derived features only (as can be obtained directly from a mention annotated corpus) brings the system performance at the one obtained in the target language by using feature derived from many linguistic resources, therefore improving the system when such resources are not available.
Starting Page	314
Ending Page	324
Page Count	11
File Format	PDF
ISSN	23299290
e-ISSN	23299304
DOI	10.1109/TASLP.2013.2287055
Volume Number	22
Issue Number	2
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-02-01
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Aligned-Parallel-Corpora Based Semi-Supervised Learning for Arabic Mention Detection

Cooperative learning and its application to emotion recognition from speech

Cooperative Learning and its Application to Emotion Recognition from Speech

On training targets for supervised speech separation

Multiview supervised dictionary learning in speech emotion recognition

On Training Targets for Supervised Speech Separation

Distributed feature representations for dependency parsing

Multiview Supervised Dictionary Learning in Speech Emotion Recognition

HMM-based speech segmentation: improvements of fully automatic approaches

Aligned-Parallel-Corpora Based Semi-Supervised Learning for Arabic Mention Detection

Similar Documents

Aligned-Parallel-Corpora Based Semi-Supervised Learning for Arabic Mention Detection

Cooperative learning and its application to emotion recognition from speech

Cooperative Learning and its Application to Emotion Recognition from Speech

On training targets for supervised speech separation

Multiview supervised dictionary learning in speech emotion recognition

On Training Targets for Supervised Speech Separation

Distributed feature representations for dependency parsing

Multiview Supervised Dictionary Learning in Speech Emotion Recognition

HMM-based speech segmentation: improvements of fully automatic approaches

Aligned-Parallel-Corpora Based Semi-Supervised Learning for Arabic Mention Detection