IN2013MU03833A - System and method for crowd noise classification - Google Patents

System and method for crowd noise classification

Info

Publication number
IN2013MU03833A
IN2013MU03833A IN3833/MUM/2013A IN3833MU2013A IN2013MU03833A IN 2013MU03833 A IN2013MU03833 A IN 2013MU03833A IN 3833MU2013 A IN3833MU2013 A IN 3833MU2013A IN 2013MU03833 A IN2013MU03833 A IN 2013MU03833A
Authority
IN
India
Prior art keywords
features
classification
noise data
noise
respect
Prior art date
Application number
IN3833/MUM/2013A
Inventor
Ramu Reddy Vempada
Aniruddha Sinha
Guruprasad Seshadri
Original Assignee
Tata Consultancy Services Limited
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tata Consultancy Services Limited filed Critical Tata Consultancy Services Limited
Priority to IN2013MU000003833 priority Critical
Priority to IN3833/MUM/2013A priority patent/IN2013MU03833A/en
Publication of IN2013MU03833A publication Critical patent/IN2013MU03833A/en

Links

Classifications

    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/48Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use
    • G10L25/51Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/03Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters
    • G10L25/09Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters the extracted parameters being zero crossing rates
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/03Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters
    • G10L25/24Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters the extracted parameters being the cepstrum
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6234Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a discrimination criterion, e.g. discriminant analysis

Abstract

System(s) and method(s) for classifying noise data of human crowd are disclosed. Noise data is captured from one or more sources and features are extracted by using computation techniques. The features comprise spectral domain features and time domain features. Classification models are developed by using each of the spectral domain features and the time domain features. Discriminative information with respect to the noise data is extracted by using the classification models. A performance matrix is computed for each of the classification model. The performance matrix comprises classified noise elements with respect to the noise data. Each classified noise element is associated with a classification performance score with respect to a spectral domain feature, a time domain feature, and fusion of features and scores. The classified noise elements provide the classification of the noise data. [To be published with figure 3]
IN3833/MUM/2013A 2013-12-06 2013-12-06 System and method for crowd noise classification IN2013MU03833A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
IN2013MU000003833 2013-12-06
IN3833/MUM/2013A IN2013MU03833A (en) 2013-12-06 2013-12-06 System and method for crowd noise classification

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
IN3833/MUM/2013A IN2013MU03833A (en) 2013-12-06 2013-12-06 System and method for crowd noise classification
EP14867853.5A EP3078026A4 (en) 2013-12-06 2014-12-03 System and method to provide classification of noise data of human crowd
US15/101,817 US10134423B2 (en) 2013-12-06 2014-12-03 System and method to provide classification of noise data of human crowd
PCT/IB2014/066538 WO2015083091A2 (en) 2013-12-06 2014-12-03 System and method to provide classification of noise data of human crowd

Publications (1)

Publication Number Publication Date
IN2013MU03833A true IN2013MU03833A (en) 2015-07-31

Family

ID=53274234

Family Applications (1)

Application Number Title Priority Date Filing Date
IN3833/MUM/2013A IN2013MU03833A (en) 2013-12-06 2013-12-06 System and method for crowd noise classification

Country Status (4)

Country Link
US (1) US10134423B2 (en)
EP (1) EP3078026A4 (en)
IN (1) IN2013MU03833A (en)
WO (1) WO2015083091A2 (en)

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US7668790B2 (en) * 2006-07-27 2010-02-23 The United States Of America As Represented By The Secretary Of The Navy System and method for fusing data from different information sources with shared-sampling distribution based boosting
US8457768B2 (en) * 2007-06-04 2013-06-04 International Business Machines Corporation Crowd noise analysis
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EP2356763A1 (en) * 2008-12-08 2011-08-17 BAE Systems Information and Electronic Systems Integration Inc. Method for collaborative discrimation between authentic and spurious signals in a wireless cognitive network
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US8762144B2 (en) * 2010-07-21 2014-06-24 Samsung Electronics Co., Ltd. Method and apparatus for voice activity detection
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EP2523149A3 (en) * 2011-05-11 2017-05-24 Tata Consultancy Services Ltd. A method and system for association and decision fusion of multimodal inputs
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WO2013105108A1 (en) * 2011-11-09 2013-07-18 Tata Consultancy Services Limited A system and method for enhancing human counting by fusing results of human detection modalities
KR101892733B1 (en) * 2011-11-24 2018-08-29 한국전자통신연구원 Voice recognition apparatus based on cepstrum feature vector and method thereof
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US20150110277A1 (en) * 2013-10-22 2015-04-23 Charles Pidgeon Wearable/Portable Device and Application Software for Alerting People When the Human Sound Reaches the Preset Threshold

Also Published As

Publication number Publication date
EP3078026A2 (en) 2016-10-12
US20160307582A1 (en) 2016-10-20
US10134423B2 (en) 2018-11-20
WO2015083091A2 (en) 2015-06-11
WO2015083091A3 (en) 2015-09-24
EP3078026A4 (en) 2017-05-17

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