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Adaptation techniques for speech synthesis in under-resoured languages
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In: http://www.cs.cmu.edu/~gopalakr/publications/sltu2010_anumanchipalli.pdf (2010)
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| 82 |
ENGLISH SPOKEN TERM DETECTION IN MULTILINGUAL RECORDINGS
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In: http://publications.idiap.ch/downloads/reports/2010/Motlicek_Idiap-RR-21-2010.pdf (2010)
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| 83 |
VI Jornadas en Tecnología del Habla and II Iberian SLTech Workshop Speed Up Strategies for the Creation of Multimodal and Multilingual Dialogue Systems
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In: http://lorien.die.upm.es/%7Elfdharo/Papers/PhDThesis_Fala2010.pdf (2010)
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| 84 |
Using n-best recognition output for extractive summarization and keyword extraction in meeting speech
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In: http://www.hlt.utdallas.edu/~shasha/papers/icassp2010_liu.pdf (2010)
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| 85 |
Context preserving dynamic word cloud visualization
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In: http://research.microsoft.com/en-us/um/people/shliu/cui_pacificvis10.pdf (2010)
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| 86 |
United Kingdom (2009)" Cued Speech Recognition for Augmentative Communication in Normal-hearing and Hearing-impaired Subjects
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In: http://hal.archives-ouvertes.fr/docs/00/45/11/30/PDF/interspeech2009.pdf (2010)
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| 87 |
The CHiME corpus: a resource and a challenge for Computational Hearing in Multisource Environments
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In: http://www.dcs.shef.ac.uk/%7Ening/pubs/christensen2010-chime.pdf (2010)
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| 88 |
Speaker identification with distant microphone speech
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In: http://www.cs.cmu.edu/~kornel/pubs/0004518.pdf (2010)
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| 89 |
Content Modeling Paradigm: An Interplay of Relationship between Author, Document, Topic, and Words
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In: http://www.ijcaonline.org/casct/number2/SPE40T.pdf (2010)
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Abstract:
For any work of literature, a fundamental issue is to identify the individual(s) who wrote it, and conversely, to identify all of the works that belong to a given individual or to identify the individual who writes many papers on same topic or to identify the topics name that an author works on. Information extraction techniques (such as Author Name and Topic Recognition) have long been used to extract useful pieces of information from text. The types of information to be extracted are generally fixed and well defined. However in some cases, the user goal is more abstract and information types cannot be narrowly defined. For example, a reader of online user reviews typically has the goal of making a good choice and is interested to learn about the different aspects of a topic and author relation (e.g., famous author of a topic, author’s papers with his research field). Some of these aspects may be known by the reader and some others may need to be discovered from the inherent text structure in a large collection. Even for the known aspects (such as “author name ” and “topic”), the challenge is to recognize various hidden aspects like number of papers written by an author, his research field, popularity of an author. In this paper, we will develop content modeling Paradigm to extract the relationship between the author, document, topic and Words as topics with identifiable word distributions across documents of various authors. We review several probabilistic graphical models (such as Latent Dirichlet Allocation) and propose a new model called content modeling paradigm which is based on frequency of the words within the document.
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Keyword:
ATP Model; Index Terms — Data mining; TAP Model
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.5058
http://www.ijcaonline.org/casct/number2/SPE40T.pdf
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| 90 |
Development of a Computer-Aided Language Learning System for
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In: http://speechprosody2010.illinois.edu/papers/100983.pdf (2010)
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| 91 |
The CHiME corpus: a resource and a challenge for computational hearing in multisource environments
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In: http://staffwww.dcs.shef.ac.uk/people/J.Barker/pubs/Christensen2010is.pdf (2010)
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| 92 |
When intonation plays the main character: information-vs. confirmation- seeking questions in Majorcan Catalan
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In: https://hal.archives-ouvertes.fr/hal-01678574 ; France. 2010, Speech Prosody 2010 (2010)
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| 93 |
Discrimination of speech and non-linguistic vocalizations by non-negative matrix factorization
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In: http://www.mmk.ei.tum.de/publ/pdf/10/10sch5.pdf (2010)
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| 94 |
Creating a linguistic plausibility dataset with non-expert annotators
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In: http://mlsp.cs.cmu.edu/publications/pdfs/p17190.pdf (2010)
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| 95 |
Prosodic Focus in Hong Kong Cantonese without Post-focus Compression
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In: http://www.phon.ucl.ac.uk/home/yi/yispapers/Wu_Xu_SP2010.pdf (2010)
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| 96 |
Automatic Ontology Matching Via Upper Ontologies: A Systematic Evaluation
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In: http://www.disi.unige.it/person/MascardiV/Download/TKDE-maggio-2009.pdf (2009)
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| 97 |
Studying L2 suprasegmental features in Asian Englishes: a position paper
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In: http://www.ling.sinica.edu.tw/eip/files/publish/2009.9.17.7807558.69687253.pdf (2009)
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| 98 |
The semi-supervised switchboard transcription project
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In: http://melodi.ee.washington.edu/~bilmes/mypubs/subramanya2009-s3tp.pdf (2009)
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| 99 |
A comparison of query-by-example methods for spoken term detection
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In: http://www.ll.mit.edu/mission/communications/ist/publications/2009_09_01_Shen_Interspeech_MS-38023.pdf (2009)
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| 100 |
Complex Cepstrum-based Decomposition of Speech for Glottal Source Estimation
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In: http://tcts.fpms.ac.be/~drugman/files/IS09-ComplexCepstrum.pdf (2009)
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