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1
The Twins corpus of museum visitor questions
In: http://people.ict.usc.edu/~traum/Papers/twins-corpus.pdf (2012)
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2
Morphological variation in the adult vocal tract: A study using rtmri
In: http://mproctor.net/docs/lammert11_IS2011_morphology.pdf (2011)
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3
Direct Estimation of Articulatory Kinematics from Real-time Magnetic Resonance Image Sequences
In: http://mproctor.net/docs/proctor11_IS2011_constriction.pdf (2011)
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4
A multimodal real-time MRI articulatory corpus for speech research
In: http://mproctor.net/docs/narayanan11_IS2011_MRI-TIMIT.pdf (2011)
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5
Para-linguistic mechanisms of production in human ’beatboxing’: a real-time mri study
In: http://mproctor.net/docs/proctor10_IS2010_beatboxing.pdf (2010)
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6
Rapid semiautomatic segmentation of real-time Magnetic Resonance Images for parametric vocal tract analysis
In: http://mproctor.net/docs/proctor10_IS2010_segmentation.pdf (2010)
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7
Connecting rhythm and prominence in automatic ESL pronunciation scoring
In: http://www.josephtepperman.com/nava_rhythm_2009.pdf (2009)
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8
Analysis of emotionally salient aspects of fundamental frequency for emotion detection
In: http://www.utdallas.edu/dept/eecs/research/researchlabs/msp-lab/publications/Busso_2009.pdf (2009)
Abstract: Abstract—During expressive speech, the voice is enriched to convey not only the intended semantic message but also the emotional state of the speaker. The pitch contour is one of the important properties of speech that is affected by this emotional modulation. Although pitch features have been commonly used to recognize emotions, it is not clear what aspects of the pitch contour are the most emotionally salient. This paper presents an analysis of the statistics derived from the pitch contour. First, pitch features derived from emotional speech samples are compared with the ones derived from neutral speech, by using symmetric Kullback–Leibler distance. Then, the emotionally discriminative power of the pitch features is quantified by comparing nested logistic regression models. The results indicate that gross pitch contour statistics such as mean, maximum, minimum, and range are more emotionally prominent than features describing the
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.476.3793
http://www.utdallas.edu/dept/eecs/research/researchlabs/msp-lab/publications/Busso_2009.pdf
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9
Automatic classification of question turns in spontaneous speech using lexical and prosodic evidence
In: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2631211/pdf/nihms54014.pdf (2008)
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10
An empirical analysis of user uncertainty in problem-solving child–machine interactions
In: http://care.usc.edu/research/Papers/MattJeannette-Uncertainty.pdf (2008)
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11
A text-free approach to assessing nonnative intonation
In: http://sail.usc.edu/publications/tepperman_intonation_icslp07.pdf (2007)
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12
An English-Persian Automatic Speech Translator: Recent Developments in Domain Portability and User Modeling
In: http://sail.usc.edu/publications/georgiou_isyc2006_s2s.pdf (2006)
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13
Abstract
In: http://sail.usc.edu/publications/Sethy-SpeechComm2006.pdf (2006)
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14
Combining acoustic, lexical, and syntactic evidence for automatic unsupervised prosody labeling
In: http://sail.usc.edu/publications/ananthak_icslp06.pdf (2006)
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15
Detection of Non-Native Named Entities Using Prosodic Features for Improved Speech Recognition and Translation
In: http://isca-speech.org/archive_open/archive_papers/ml06/ml06_003.pdf (2006)
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16
Vector-based representation and clustering of audio using onomatopoeia words
In: https://www.aaai.org/Papers/Symposia/Fall/2006/FS-06-01/FS06-01-012.pdf (2006)
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17
Pronunciation verification of children’s speech for automatic literacy assessment
In: http://www.seas.ucla.edu/spapl/paper/alwan_icslp_06.pdf (2006)
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18
Tactical Language detection and modeling of learner speech errors: The case of Arabic tactical language training for American English speakers
In: http://www.alelo.com/files/INSTIL04-tactical_language_detection.pdf (2004)
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19
Tactical language detection and modeling of learner speech errors: The case of Arabic tactical language training for American English speakers
In: http://isca-speech.org/archive_open/archive_papers/icall2004/iic4_012.pdf (2004)
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20
A transcription scheme for languages employing the arabic script motivated by speech processing application
In: http://www.aclweb.org/anthology-new/W/W04/W04-1611.pdf (2004)
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