Please wait, while we are loading the content...
Please wait, while we are loading the content...
Content Provider | IEEE Xplore Digital Library |
---|---|
Author | Xiaodong Cui Alwan, A. |
Copyright Year | 1993 |
Abstract | A feature compensation (FC) algorithm based on polynomial regression of utterance signal-to-noise ratio (SNR) for noise robust automatic speech recognition (ASR) is proposed. In this algorithm, the bias between clean and noisy speech features is approximated by a set of polynomials which are estimated from adaptation data from the new environment by the expectation-maximization (EM) algorithm under the maximum likelihood (ML) criterion. In ASR, the utterance SNR for the speech signal is first estimated and noisy speech features are then compensated for by regression polynomials. The compensated speech features are decoded via acoustic HMMs trained with clean data. Comparative experiments on the Aurora 2 (English) and the German part of the Aurora 3 databases are performed between FC and maximum likelihood linear regression (MLLR). With the Aurora2 experiments, there are two MLLR implementations: pooling adaptation data across all SNRs, and using three distinct SNR clusters. For each type of noise, FC achieves, on average, a word error rate reduction of 16.7% and 16.5% for Set A, and 20.5% and 14.6% for Set B compared to the first and second MLLR implementations, respectively. For each SNR condition, FC achieves, on average, a word error rate reduction of 33.1% and 34.5% for Set A, and 23.6% and 21.4% for Set B. Results using the Aurora3 database show that, the best FC performance outperforms MLLR by 15.9%, 3.0% and 14.6% for well-matched, medium-mismatched and high-mismatched conditions, respectively. |
Starting Page | 1161 |
Ending Page | 1172 |
Page Count | 12 |
File Size | 678802 |
File Format | |
ISSN | 10636676 |
Volume Number | 13 |
Issue Number | 6 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-11-01 |
Publisher Place | U.S.A. |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Noise robustness Speech recognition Polynomials Signal to noise ratio Maximum likelihood linear regression Working environment noise Automatic speech recognition Maximum likelihood estimation Error analysis Acoustic noise signal-to-noise ratio (SNR) estimation Feature compensation noise robust speech recognition polynomial regression |
Content Type | Text |
Resource Type | Article |
Subject | Acoustics and Ultrasonics Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
National Digital Library of India (NDLI) is a virtual repository of learning resources which is not just a repository with search/browse facilities but provides a host of services for the learner community. It is sponsored and mentored by Ministry of Education, Government of India, through its National Mission on Education through Information and Communication Technology (NMEICT). Filtered and federated searching is employed to facilitate focused searching so that learners can find the right resource with least effort and in minimum time. NDLI provides user group-specific services such as Examination Preparatory for School and College students and job aspirants. Services for Researchers and general learners are also provided. NDLI is designed to hold content of any language and provides interface support for 10 most widely used Indian languages. It is built to provide support for all academic levels including researchers and life-long learners, all disciplines, all popular forms of access devices and differently-abled learners. It is designed to enable people to learn and prepare from best practices from all over the world and to facilitate researchers to perform inter-linked exploration from multiple sources. It is developed, operated and maintained from Indian Institute of Technology Kharagpur.
Learn more about this project from here.
NDLI is a conglomeration of freely available or institutionally contributed or donated or publisher managed contents. Almost all these contents are hosted and accessed from respective sources. The responsibility for authenticity, relevance, completeness, accuracy, reliability and suitability of these contents rests with the respective organization and NDLI has no responsibility or liability for these. Every effort is made to keep the NDLI portal up and running smoothly unless there are some unavoidable technical issues.
Ministry of Education, through its National Mission on Education through Information and Communication Technology (NMEICT), has sponsored and funded the National Digital Library of India (NDLI) project.
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 |
Loading...
|