NDLI: Comparing Two Models for Word Boundary Detection in a Phoneme Sequence Using Recurrent Fuzzy Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Derakhshi, M.R.F. Kangavari, M.R. Moattar, E.Z. Shorehdeli, M.A.
Copyright Year	2007
Description	Author affiliation: Univ. of Tabriz, Tabriz (Derakhshi, M.R.F.)
Abstract	The word boundary detection has an application in speech processing systems. The problem this paper tries to solve is to separate words of a sequence of phonemes where there is no delimiter between phonemes. This paper tries to compare two conceptual models for word boundary detection, named preorder and postorder models. In this paper, at first, a recurrent fuzzy neural network (RFNN) together with its relevant structure is proposed and learning algorithm is presented. Next, this RFNN is used to post-detecting word boundaries. Some experiments have already been implemented to determine complete structure of RFNN in both models. Here in this paper, three methods are proposed to encode input phoneme and their performance have been evaluated. Some experiments have been conducted to determine required number of fuzzy rules and then performance of RFNN in postdetecting word boundaries is tested in both models. Preorder model shows better performance than postorder model in experiments.
Starting Page	178
Ending Page	182
File Size	928232
Page Count	5
File Format	PDF
ISBN	9781424418404
DOI	10.1109/IIT.2007.4430431
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-18
Publisher Place	Dubai
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Infrared detectors Vocabulary Recurrent fuzzy neural network Decoding Application software Computer science Fuzzy logic Databases Speech recognition Fuzzy neural networks Word boundary detection Computer networks Natural language processing Fuzzy neural network Speech processing
Content Type	Text
Resource Type	Article

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

Large vocabulary speed recognition using neural-fuzzy and concept networks

Application of neural network and fuzzy inference to Chinese-Phoneme recognition

Modular-Based Classifier for Phoneme Recognition

Recurrent neural network with both side input context dependence for text-to-phoneme mapping

Automatic language identification with recurrent neural networks

Recurrent Neural Networks For Phoneme Recognition (1994)

Fuzzy logic-based natural language processing and its application to speech recognition.

A neural network for 500 vocabulary word spotting using acoustic sub-word units

Recurrent fuzzy logic in speech recognition

Comparing Two Models for Word Boundary Detection in a Phoneme Sequence Using Recurrent Fuzzy Neural Networks

Similar Documents

Large vocabulary speed recognition using neural-fuzzy and concept networks

Application of neural network and fuzzy inference to Chinese-Phoneme recognition

Modular-Based Classifier for Phoneme Recognition

Recurrent neural network with both side input context dependence for text-to-phoneme mapping

Automatic language identification with recurrent neural networks

Recurrent Neural Networks For Phoneme Recognition (1994)

Fuzzy logic-based natural language processing and its application to speech recognition.

A neural network for 500 vocabulary word spotting using acoustic sub-word units

Recurrent fuzzy logic in speech recognition

Comparing Two Models for Word Boundary Detection in a Phoneme Sequence Using Recurrent Fuzzy Neural Networks