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The Pennsylvania State University CiteSeerX Archives (11)
Aimee Chin (1)
Alicia Burga (1)
Amanda Müller (1)
Anusha Raghunathan (1)
Ar Hayat Khiyal (1)
Chinhui Juhn (1)
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2011 (11)
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Online (11)
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Simple Search
Hits 1 – 11 of 11
1
The Corpus of Academic Learner English (CALE): A new resource for the study of lexico-grammatical variation in advanced learner varieties
Marcus Callies
;
Ekaterina Zaytseva
In: http://www.staff.uni-mainz.de/mcallies/papers/Callies%26Zaytseva2011.pdf (2011)
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2
Towards the Annotation of Communicative Structure in Corpora
Alicia Burga
;
Simon Mille
;
Leo Wanner
In: http://meaningtext.net/mtt2011/proceedings/papers/BurgaMilleWanner.pdf (2011)
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3
EVALUATION OF INTELLIGIBILITY AND SPEAKER SIMILARITY OF
Anusha Raghunathan
In: http://uknowledge.uky.edu/cgi/viewcontent.cgi?article%3D1099%26context%3Dgradschool_theses (2011)
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4
L1 transfer in article selection for generic reference by Spanish, Turkish and Japanese L2 learners
English Studies Ijes
;
Neal Snape
;
María Del
...
In: http://revistas.um.es/ijes/article/download/138701/147991/ (2011)
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5
Translation Rules and ANN Based Model for English to Urdu Machine Translation
R. B. Mishra
In: http://www.dcc.ufla.br/infocomp/images/artigos/v10.3/art04.pdf (2011)
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6
Forensic Voice Comparison using Chinese /iau
Cuiling Zhang
;
Geoffrey Stewart Morrison
;
Tharmarajah Thiruvaran
In: http://geoff-morrison.net/documents/Zhang,+Morrison,+Thiruvaran+%282011%29+Forensic+voice+comparison+using+Chinese+-iau-.pdf (2011)
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7
Voice Recognition using HMM with MFCC for secure ATM”,IJCS Vol.8,Issue 6
Shumaila Iqbal
;
Tahira Mahboob
;
Malik Sik
;
Ar Hayat Khiyal
In: http://www.ijcsi.org/papers/IJCSI-8-6-3-297-303.pdf (2011)
Abstract:
Security is an essential part of human life. In this era security is a huge issue that is reliable and efficient if it is unique by any mean. Voice recognition is one of the security measures that are used to provide protection to human’s computerized and electronic belongings by his voice. In this paper voice sample is observed with MFCC for extracting acoustic features and then used to trained HMM parameters through forward backward algorithm which lies under HMM and finally the computed log likelihood from training is stored to database. It will recognize the speaker by comparing the log value from the database against the PIN code. It is implemented in Matlab 7.0 environment and showing 86.67 % results as correct acceptance and correct rejections with the error rate of
Keyword:
Discrete Cosine Transform
;
Fast Fourier Transform
;
Forward Backward algorithm
;
Hidden Markov Modeling
;
K-mean algorithm
;
Mel Frequency Cepstral coefficients
;
Voice recognition
URL:
http://www.ijcsi.org/papers/IJCSI-8-6-3-297-303.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.403.3592
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8
Association for Academic Language and Learning
Amanda Müller
In: http://journal.aall.org.au/index.php/jall/article/viewFile/145/122/ (2011)
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9
Ukp at crosslink: Anchor text translation for cross-lingual link discovery
Jungi Kim
;
Iryna Gurevych
In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings9/NTCIR/07-NTCIR9-CROSSLINK-KimJ.pdf (2011)
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10
The Returns to English-Language Skills in India
Mehtabul Azam
;
Aimee Chin
;
Nishith Prakash
...
In: http://www.iza.org/conference_files/ESSLE2011/prakash_n5110.pdf (2011)
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11
Examining the Generality of Self-Explanation
Ruth Wylie
In: http://reports-archive.adm.cs.cmu.edu/anon/hcii/CMU-HCII-11-105.pdf (2011)
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