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Theune, M., Klabbers, E., Odijk, J., De Pijper, J.R., and Krahmer, E.: From Data to Speech: A General Approach. Natural Language Engineering, 7(1), (2001) 47--86.

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SumTime-Turbine: A Knowledge-Based System to.. - Yu, Reiter, Hunter.. (2003)   (Correct)

....of which are RESUME, GoalGetter, and SumTime Mousam. RESUME [4] uses KBTA method to create temporal abstractions from medical data. The KBTA framework provides the most comprehensive starting point for generating summaries of temporal data, however, doesn t produce textual summaries. GoalGetter [7] is a data to speech system, which generates Dutch spoken summaries of football matches. But the input data to SumTime Turbine is complex highfrequency multi channel time series data instead of teletext. SumTime Mousam [6] generates textual weather forecasts for the offshore oil rig applications ....

M. Theune, E. Klabbers (2001) " From Data to Speech: A General Approach", Natural Language Engineering 7(1): 47-86


SumTime-Turbine: A Knowledge-Based System to.. - Yu, Reiter, Hunter.. (2003)   (Correct)

....which are RESUME, GoalGetter, and SumTime Mousam. RESUME [4] uses KBTA method to create temporal abstractions from medical data. The KBTA framework provides the most comprehensive starting point for generating summaries of temporal data. However, it doesn t produce textual summaries. GoalGetter [7] is a data to speech system, which generates Dutch spoken summaries of football matches. Its input data is teletext, while the input data of SumTimeTurbine is complex high frequency multi channel time series data. SumTime Mousam [6] generates textual weather forecasts for the offshore oil rig ....

M. Theune, E. Klabbers (2001), From Data to Speech: A General Approach, Natural Language Engineering 7(1): 47-86


Symbolic Authoring for Multilingual Natural Language Generation - Androutsopoulos, al. (2002)   (Correct)

....of the object using natural language generation techniques, to be discussed briefly below. In virtual reality environments, the description is then passed to a speech synthesizer, which produces the audio output, exploiting additional markup made available by the generation components, much as in [18]. visitor object selection , O Q author I speech h I , subsystem I (text or speech) Fig. 3. The authoring subsystem in M PIRO s architecture Many of the linguistic resources on which the generation process relies, most notably its systemic grammars [5, 6] are to a large extent ....

M. Theune, E. Klabbers, J.R. De Pijper, E. Krahmer and J. Odijk. "from Data to Speech: A General Approach". Natural Language Engineering, 7(1 ):47-86, 2001.


Generating Multilingual Personalized Descriptions.. - Androutsopoulos.. (2001)   (5 citations)  (Correct)

....by computer means that significant additional information can be provided to the synthesizer. Factors such as phrasal boundaries, rhetorical relations between phrases, and whether some item of information has been previously expressed can then be taken into account in producing synthesized speech [Theune et al. 2001]. This approach is expected to lead to improved prosody, adding to the acceptability of the system in real usage scenarios. 4. Interactive symbolic authoring Let us now examine more closely M PIRO s authoring tool (see Figure 1) The tool is intended to be used at two stages: domain authoring ....

M. Theune, E. Klabbers, J.R. De Pijper, E. Krahmer and J. Odijk. "From Data to Speech: A General Approach". Natural Language Engineering, 7(1):47-86, 2001.


ANGELICA Choice of output modality in an embodied agent - Theune   Self-citation (Theune)   (Correct)

No context found.

Theune, M., E. Klabbers, J.R. de Pijper, E. Krahmer and J. Odijk. From data to speech: A general approach. Natural Language Engineering 7, 1 (2001), 47-86.


Modeling Prosodic Structures in Linguistically.. - Xydas.. (2004)   (Correct)

No context found.

Theune, M., Klabbers, E., Odijk, J., De Pijper, J.R., and Krahmer, E.: From Data to Speech: A General Approach. Natural Language Engineering, 7(1), (2001) 47--86.


Prosody Prediction from Linguistically Enriched.. - Xydas..   (Correct)

No context found.

Theune, Mariet, Esther Klabbers, Jan Od ijk, Jan Roelof De Pijper and Em iel Krahmer. 2001. From Data to Speech: A General Approach . Natural Language Engineering, 7(1):47-86.


Natural Language Engineering ??? ???--???. Printed in.. - Cambridge University..   (Correct)

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Theune, M., Klabbers, E., De Pijper, J.R., Krahmer, E. and Odijk, J. (2001) From data to speech: a general approach. Natural Language Engineering 7(1):47--86.


Modeling Prosodic Structures in Linguistically.. - Xydas.. (2004)   (Correct)

No context found.

Theune, M., Klabbers, E., Odijk, J., De Pijper, J.R., and Krahmer, E.: From Data to Speech: A General Approach. Natural Language Engineering, 7(1), (2001) 47--86.


Building Prosodic Structures in a Concept-to-Speech.. - Xydas, Spiliotopoulos.. (2003)   (Correct)

No context found.

Theune, M., Klabbers, E., Odijk, J., De Pijper, J.R., and Krahmer, E. (2001) From Data to Speech: A General Approach. Natural Language Engineering, 7(1), pp. 47-86.


Modeling Improved Prosody Generation from High-Level.. - Xydas, al. (2005)   (Correct)

No context found.

M. Theune, E. Klabbers, J. Odijk, J.R. De Pijper, and E. Krahmer, "From data to speech: A general approach," Natural Language Engineering, vol.7, no.1, pp.47--86, 2001.

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