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SPPAS - MULTI-LINGUAL APPROACHES TO THE AUTOMATIC ANNOTATION OF SPEECH ...
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SPPAS - MULTI-LINGUAL APPROACHES TO THE AUTOMATIC ANNOTATION OF SPEECH ...
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Does Vocabulary Knowledge Affect Lexical Segmentation in Adverse Conditions?
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Bishell, Michelle. - : University of Canterbury. Department of Communication Disorders, 2015
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The Effects of Sign on Speech Segmentation in Infants
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In: Open Access Theses & Dissertations (2015)
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Visual Speech Segmentation: Using Facial Cues to Locate Word Boundaries in Continuous Speech
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In: Faculty Journal Articles (2014)
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ImageSpirit: Verbal guided image parsing
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In: http://vecg.cs.ucl.ac.uk/Projects/SmartGeometry/image_spirit/paper_docs/imageSpirit_tog_14.pdf (2014)
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The exploitation of sub-phonemic acoustic detail in L2 speech segmentation
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In: ISSN: 0272-2631 ; EISSN: 1470-1545 ; Studies in Second Language Acquisition ; https://halshs.archives-ouvertes.fr/halshs-01423067 ; Studies in Second Language Acquisition, Cambridge University Press (CUP), 2014, 36 (4), pp.709-731 (2014)
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Algorithme de découpages en groupes prosodiques pour la dictée par l'usage de synthèse vocale
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In: Journées d'études sur la parole ; https://hal.archives-ouvertes.fr/hal-01137707 ; Journées d'études sur la parole, Jun 2014, Le Mans, France (2014)
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Early Word Recognition and Later Language Skills
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In: Brain Sciences ; Volume 4 ; Issue 4 ; Pages 532-559 (2014)
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Keyword Co-articulatory Boundary Segmentation of the CRM Speech Corpus
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ImageSpirit: Verbal Guided Image Parsing
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In: ACM Transactions on Graphics , 34 (1) , Article 3. (2014) (2014)
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Abstract:
Humans describe images in terms of nouns and adjectives while algorithms operate on images represented as sets of pixels. Bridging this gap between how humans would like to access images versus their typical representation is the goal of image parsing, which involves assigning object and attribute labels to pixels. In this article we propose treating nouns as object labels and adjectives as visual attribute labels. This allows us to formulate the image parsing problem as one of jointly estimating per-pixel object and attribute labels from a set of training images. We propose an efficient (interactive time) solution. Using the extracted labels as handles, our system empowers a user to verbally refine the results. This enables hands-free parsing of an image into pixel-wise object/attribute labels that correspond to human semantics. Verbally selecting objects of interest enables a novel and natural interaction modality that can possibly be used to interact with new generation devices (e.g., smartphones, Google Glass, livingroom devices). We demonstrate our system on a large number of real-world images with varying complexity. To help understand the trade-offs compared to traditional mouse-based interactions, results are reported for both a large-scale quantitative evaluation and a user study.
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Keyword:
Design; Human Factors; Image parsing; Languages; multilabel CRF; natural language control; object class segmentation; speech interface; visual attributes
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URL: http://discovery.ucl.ac.uk/1502250/ http://discovery.ucl.ac.uk/1502250/1/imageSpirit_tog_14.pdf
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Infants' Speech Segmentation: The Impact of Mother-Infant Facial Synchrony
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In: The Journal of Purdue Undergraduate Research (2014)
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Is Maternal Touch Used Referentially?
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In: Open Access Theses (2014)
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A Comparison of Open-Source Segmentation Architectures for Dealing with Imperfect Data from the Media in Speech Synthesis
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Le chunking perceptif de la parole : sur la nature du groupement temporel et son effet sur la mémoire immédiate
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Seeing Spaces: An Eye-Tracking Study Of Speech Segmentation
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In: Honors Theses (2013)
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КОНСТРУКЦИИ С ОБРЫВОМ В ПРЕДВЫБОРНЫХ ТЕЛЕДЕБАТАХ
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Лаврова, А.. - : Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования Воронежский государственный университет, 2013
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Author manuscript, published in "8th International Conference on Language Resources and Evaluation (LREC'12), Turkey (2012)" Evaluating the Impact of External Lexical Resources into a CRF-based
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In: http://hal-enpc.archives-ouvertes.fr/docs/00/79/06/24/PDF/constant-tellier-lrec2012.pdf (2013)
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Syll-O-Matic: an Adaptive Time-Frequency Representation for the Automatic Segmentation of Speech into Syllables
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In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) ; https://hal.sorbonne-universite.fr/hal-00943799 ; IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2013, Vancouver, Canada (2013)
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