NDLI: Model-based margin estimation for hidden Markov model learning and generalisation

Please wait, while we are loading the content...

Biosurface and Biotribology

CAAI Transactions on Intelligence Technology

CIRED - Open Access Proceedings Journal

Chinese Journal of Electronics

Cognitive Computation and Systems

Electronics Letters

Energy Conversion and Economics

Engineering & Technology

Engineering Biology

Healthcare Technology Letters

IET Circuits, Devices & Systems

IET Collaborative Intelligent Manufacturing

IET Communications

IET Computer Vision

IET Computers & Digital Techniques

IET Control Theory & Applications

IET Cyber-Physical Systems: Theory & Applications

IET Cyber-Systems and Robotics

IET Electric Power Applications

IET Electrical Systems in Transportation

IET Energy Systems Integration

IET Generation, Transmission & Distribution

IET Image Processing

IET Information Security

IET Intelligent Transport Systems

IET Microwaves, Antennas & Propagation

IET Nanobiotechnology

IET Nanodielectrics

IET Optoelectronics

IET Power Electronics

IET Quantum Communication

IET Radar, Sonar & Navigation

IET Renewable Power Generation

IET Science, Measurement & Technology

IET Signal Processing

Volume 15 (2021)

Volume 14 (2020)

Volume 13 (2019)

Volume 12 (2018)

Volume 11 (2017)

Volume 10 (2016)

Volume 9 (2015)

Volume 8 (2014)

Volume 7 (2013)

Volume 7 (2013) : Issue 9, Dec

Volume 7 (2013) : Issue 8, Oct

Application of continuous-time wavelet entropy for detection of cardiac repolarisation alternans

Compensated robust least-squares estimator for target localisation in sensor network using time difference of arrival measurements

Cooperative wideband sensing based on entropy and cyclic features under noise uncertainty

Double-level binary tree Bayesian compressed sensing for block structured sparse signals

High performance and low-power finite impulse response filter based on ring topology with modified retiming serial multiplier on FPGA

Identification of Hammerstein systems using key-term separation principle, auxiliary model and improved particle swarm optimisation algorithm

Improved sub-band adaptive thresholding function for denoising of satellite image based on evolutionary algorithms

Model-based margin estimation for hidden Markov model learning and generalisation

Multi-channels wideband digital reconnaissance receiver based on compressed sensing

Multiple observer design for a non-linear Takagi–Sugeno system submitted to unknown inputs and outputs

Networked ℋ ∞ filtering for discrete linear systems with a periodic event-triggering communication scheme

New inequalities on sparse representation in pairs of bases

Robust beamforming in circular arrays using phase-mode transformation

Robust l 2–l∞ filtering for discrete-time Markovian jump linear systems with multiple sensor faults, uncertain transition probabilities and time-varying delays

Robust speech recognition by using spectral subtraction with noise peak shifting

Two-stage parameter estimation algorithms for Box–Jenkins systems

Volume 7 (2013) : Issue 7, Sep

Volume 7 (2013) : Issue 6, Aug

Volume 7 (2013) : Issue 5, Jul

Volume 7 (2013) : Issue 4, Jun

Volume 7 (2013) : Issue 3, May

Volume 7 (2013) : Issue 2, Apr

Volume 7 (2013) : Issue 1, Feb

Volume 5 (2011)

Volume 4 (2010)

Volume 3 (2009)

Volume 2 (2008)

Volume 1 (2007)

IET Smart Cities

IET Systems Biology

IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Model-based margin estimation for hidden Markov model learning and generalisation

Content Provider	IET Digital Library
Author	Siniscalchi, Sabato Marco Li, Jinyu Lee, Chin Hui
Abstract	Recently, speech scientists have been motivated by the great, success of building margin-based classifiers, and have thus proposed novel methods to estimate continuous-density hidden Markov model (HMM) for automatic speech recognition (ASR) according to the notion that the decision boundaries determined by the estimated HMMs attain the maximum classification margin as in learning support vector machines. Although a good performance has been observed, the margin used in the ASR community is often specified as a parameter that has no explicit relationship with the HMM parameters. The issues of how the margin is related to the HMM parameters and how it directly characterises the generalisation capability of HMM-based classifiers have not been addressed so far in the community. In this study, the authors attempt to formulate the margin used in the soft margin estimation framework as a function of the HMM parameters. The key idea is to relate the standard distance-based margin with the concept of divergence among competing HMM state Gaussian mixture model densities. Experimental results show that the proposed model-based margin function is a good indication about the quality of HMMs on a given ASR task without the conventional needs of running experiments extensively using a separate set of test samples.
Starting Page	704
Ending Page	709
Page Count	6
ISSN	17519675
Volume Number	7
e-ISSN	17519683
Issue Number	Issue 8, Oct (2013)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/7/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2013.0036
Journal	IET Signal Processing
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ASR Automatic Speech Recognition Continuous-density Hidden Markov Estimation Model Estimation Theory Gaussian Processes Generalisation Hidden Markov Model Hidden Markov Model Learning HMM Knowledge Engineering Technique Learning in AI Learning Support Vector Machine Margin-based Classifier Markov Processes Maximum Classification Margin Model-based Margin Estimation Parameter Estimation Pattern Classification Soft Margin Estimation Framework Speech Processing Technique Speech Recognition Speech Recognition And Synthesis Speech Scientist Standard Distance-based Margin State Gaussian Mixture Model Density Support Vector Machine
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

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