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Articulatory speech synthesis ; Synthèse articulatoire de la parole
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In: https://hal.archives-ouvertes.fr/tel-02433528 ; Computation and Language [cs.CL]. Université de Lorraine, 2019. English. ⟨NNT : 2019LORR0166⟩ (2019)
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102 |
The Zero Resource Speech Challenge 2019: TTS without T
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In: Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02274112 ; Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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103 |
Modeling Labial Coarticulation with Bidirectional Gated Recurrent Networks and Transfer Learning
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In: INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-02175780 ; INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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104 |
Conditional Variational Auto-Encoder for Text-Driven Expressive AudioVisual Speech Synthesis
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In: INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-02175776 ; INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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Features of the formation of competitive stability of enterprises of rural green tourism on the principles of marketing ...
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Features of the formation of competitive stability of enterprises of rural green tourism on the principles of marketing ...
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Short-Term International Experiences in Language Teacher Education: A Qualitative Meta-Synthesis
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In: Australian Journal of Teacher Education (2019)
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108 |
Cap-Independent mRNA Translation in Germ Cells
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In: International Journal of Molecular Sciences ; Volume 20 ; Issue 1 (2019)
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109 |
Improving reporting of meta-ethnography: The eMERGe reporting guidance
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110 |
The views and experiences of suicidal children and young people of mental health support services: A meta-ethnography.
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111 |
create_vtl_corpus: Synthesizing a speech corpus with VocalTractLab ...
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112 |
Listening-test materials for "Modern speech synthesis for phonetic sciences: a discussion and an evaluation" ...
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Unkn Unknown. - : University of Edinburgh. School of Informatics. Centre for Speech Technology Research (CSTR), 2019
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CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit (version 0.92) ...
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Unkn Unknown. - : University of Edinburgh. The Centre for Speech Technology Research (CSTR), 2019
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Линия, цвет, слово: символы эпохи в работах молодых исследователей культуры ... : LINE, COLOR, WORD: EPOCH SYMBOLS IN YOUNG CULTURAL RESEARCHERS’ STUDIES ...
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117 |
Facial re-enactment, speech synthesis and the rise of the Deepfake
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In: Theses : Honours (2019)
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118 |
Trans-acting translational regulatory RNA binding proteins.
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119 |
Exploring Efficient Neural Architectures for Linguistic–Acoustic Mapping in Text-To-Speech
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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120 |
Speech Synthesis in the Translation Revision Process: Evidence from Error Analysis, Questionnaire, and Eye-Tracking
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In: Informatics ; Volume 6 ; Issue 4 (2019)
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Abstract:
Translation revision is a relevant topic for translator training and research. Recent technological developments justify increased focus on embedding speech technologies&mdash ; speech synthesis (text-to-speech) and speech recognition (speech-to-text)&mdash ; into revision workflows. Despite some integration of speech recognition into computer-assisted translation (CAT)/translation environment tools (TEnT)/Revision tools, to date we are unaware of any CAT/TEnT/Revision tool that includes speech synthesis. This paper addresses this issue by presenting initial results of a case study with 11 participants exploring if and how the presence of sound, specifically in the source text (ST), affects revisers&rsquo ; revision quality, preference and viewing behaviour. Our findings suggest an improvement in revision quality, especially regarding Accuracy errors, when sound was present. The majority of participants preferred listening to the ST while revising, but their self-reported gains on concentration and productivity were not conclusive. For viewing behaviour, a subset of eye-tracking data shows that participants focused more on the target text (TT) than the source regardless of the revising condition, though with differences in fixation counts, dwell time and mean fixation duration (MDF). Orientation and finalisation phases were also identified. Finally, speech synthesis appears to increase perceived alertness, and may prompt revisers to consult external resources more frequently.
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Keyword:
computer-assisted translation (CAT); error analysis; error detection; eye-tracking; speech synthesis; translation revision
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URL: https://doi.org/10.3390/informatics6040051
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