NDLI: Amplification of signal features using variance fractal dimension trajectory

Content Provider	IEEE Xplore Digital Library
Author	Kinsner, W. Grieder, W.
Copyright Year	2009
Description	Author affiliation: Signal and Data Compression Laboratory, Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada R3T 5V6 (Kinsner, W.; Grieder, W.)
Abstract	This paper describes how the selection of parameters for the variance fractal dimension (VFD) multiscale time-domain algorithm can create an amplification of the fractal dimension trajectory that is obtained for a natural-speech waveform in the presence of ambient noise. The technique is based on the variance fractal dimension trajectory (VFDT) algorithm that is used not only to detect the external boundaries of an utterance, but also its internal pauses representing the unvoiced speech. The VFDT algorithm can also amplify internal features of phonemes. This fractal feature amplification is accomplished when the time increments are selected in a dyadic manner rather than selecting the increments in a unit distance sequence. These amplified trajectories for different phonemes are more distinct, thus providing a better characterization of the individual segments in the speech signal. This approach is superior to other energy-based boundary-detection techniques. These observations are based on extensive experimental results on speech utterances digitized at 44.1 kilosamples per second, with 16 bits in each sample.
Starting Page	201
Ending Page	209
File Size	5701881
Page Count	9
File Format	PDF
ISBN	9781424446421
DOI	10.1109/COGINF.2009.5250750
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-15
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fractals Speech analysis Pattern matching Signal processing Magnetic materials Automatic speech recognition Natural languages Feature extraction Speech recognition Linear predictive coding speech utterance characterization Fractal measures fractal variance dimension trajectory fractal feature extraction feature amplification
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

Speech segmentation using multifractal measures and amplification of signal features

Speaker Recognition Using Spectral Dimension Features

A Comparative Study of Feature Extraction Methods Applied to Continuous Speech Recognition in Romanian Language

Multi-agent Based Arabic Speech Recognition

Multi-agent Based Arabic Speech Recognition

Feature extraction and recognition of infant cries

Speech recognition using dynamic neural networks

Fractal modelling of residues in linear predictive coding of speech

The optimization of perceptually-based features for speaker identification

Amplification of signal features using variance fractal dimension trajectory

Similar Documents

Speech segmentation using multifractal measures and amplification of signal features

Speaker Recognition Using Spectral Dimension Features

A Comparative Study of Feature Extraction Methods Applied to Continuous Speech Recognition in Romanian Language

Multi-agent Based Arabic Speech Recognition

Multi-agent Based Arabic Speech Recognition

Feature extraction and recognition of infant cries

Speech recognition using dynamic neural networks

Fractal modelling of residues in linear predictive coding of speech

The optimization of perceptually-based features for speaker identification

Amplification of signal features using variance fractal dimension trajectory