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A corpus-based speech synthesis system with emotion.

Preface.Foreword.1. Reducing Discontinuities at Synthesis Time for Corpus-Based Speech Synthesis.Introduction.Shift-Only F0 Smoothing.Improving Quality of MBROLA Synthesis.Evaluation.Discussions and Conclusion.Bibliography.2. Voice Quality Variation in a Long-Term Recording of a Single Speaker Speech Corpus.Introduction.Perceptual Experiment.Factors of Voice Quality Variation.Candidates of Acoustic Correlates.Prediction of Voice Quality Difference Scores.Summary.Bibliography.3. Join Cost for Unit Selection Speech Synthesis.Introduction.Previous Work.Spectral Distances.Perceptual Listening Tests.Results and Discussion.Conclusions.Bibliography.4. Articulatory Modeling: A Role in Concatenative Text to Speech Synthesis.Introduction.Articulatory Modeling.Rule-Based Control of the Parameters.Concatenative Articulatory Synthesis.Concluding Remarks.Bibliography.5. Minimizing The Amount of Pitch Modification in Speech Synthesis.Introduction.Speech Corpus Analysis.Text Corpus Analysis.Perceptual Experiment.Conclusion.Bibliography.6. The Use of Speech Recognition Technology in Speech Synthesis.Introduction.Speech Recognition.ASR in Synthesis.Limitations.Speculations.Bibliography.7. An HMM-Based Approach to Multilingual Speech Synthesis.Introduction.HMM-Based Speech Synthesis System.F0 Pattern Modeling by HMM.Speech-Parameter Generation from an HMM.Implementation on Festival Architecture.Discussion.Conclusion.Bibliography.8. Prosody Control For HMM-Based Japanese TTS.Introduction.Outline of HMM-Based TTS System.Prosody Generation Using the Quantification Theory (Type 1).Speech-Rate-Variable Synthesis Method.Conclusions.Bibliography.9. Synthesizing Expressive Speech Overview: Challenges, and Open Questions.Introduction.Theories of Emotion.Dimensions of Emotional Space.Speech Synthesis Methods.Emotional Speech Data Collection.Experimental Evaluation of Expressive Speech.Presentation of Results From Case Studies.Conclusion.Open Questions and Future Directions.Bibliography.10. Unit Selection Synthesis of Prosody: Evaluation Using Diphone Transplantation.Introduction.Computing Prosody by Selection.Comparative Evaluation.Results.Conclusion.Bibliography.11. Toward Expressive Synthetic Speech.Introduction.A Pilot Study For Generating Expressive Speech.Generating Expressive Speech with Limited Resources.Rule-Based Methods for Generating Expressive Speech.Use of an Expressive TTS System.Assessing Performance.Conclusions.Bibliography.Footnotes.Copyright Forms.References.Index.

A speech synthesis system with emotion for assisting communication.

The current focus for our research includes the role of emotion, expression and gesture in our agents/companions, the explicit teaching of such social skills as recognizing and displaying appropriate expressions/gestures, and the integration of template/database-based dialogue managers with more conversational TT/LP systems as well as with audio-visual speech/gesture recognition/synthesis technologies.

“ A corpus-based speech synthesis system ..

We define CONE B3 and CONE CEAF metrics based on the traditional B3 and CEAF metrics and show that CONE B3 and CONE CEAF scores of any CRR system on any dataset are highly correlated with its B3 and CEAF scores respectively.

A further problem with most definitions of EF is the relative dearth of attention given to emotional and motivational aspects of self-regulation. While this is certainly discussed by Luria (1966) and others who described the consequences of frontal lobe injuries in humans and primates (Damasio, 1994; Dimond, 1980; Fuster, 1997; Stuss & Benson, 1986) it has been largely ignored in most other conceptualizations of EF in the past 20 years. This is particularly so in accounts of EF using cognitive psychology and information processing models. Exceptions have been Fuster's theory of cross-temporal synthesis (1997), Damasio's (1994) somatic marker theory, Stuss and Benson's (1986) hierarchical model, and my own hybrid model of EF (Barkley, 1997a, 1997b). None are based on the computer metaphor of brain functioning that underlies information processing models of EF. Perhaps this is because computers do not have emotions that need self-regulating and do not have to self-motivate.

Large Source Corpus–Based Emotional Speech Synthesis; ..

This course covers core subject matter common to the fields of robotics, character animation and embodied intelligent agents. The intent of the course is to provide the student with a solid technical foundation for developing, animating and controlling articulated systems used in interactive computer games, virtual reality simulations and high-end animation applications. The course balances theory with practice by "looking under the hood" of current animation systems and authoring tools and exams the technologies and techniques used from both a computer science and engineering perspective. Topics covered include: geometric coordinate systems and transformations; quaternions; parametric curves and surfaces; forward and inverse kinematics; dynamic systems and control; computer simulation; keyframe, motion capture and procedural animation; behavior-based animation and control; facial animation; smart characters and intelligent agents.

A widely cited theory of PFC functioning that similarly deals with goal-directed behavior is Fuster's model of cross-temporal synthesis or integration (1997). Cross-temporal synthesis is based on three PFC components: (1) working memory, which is a temporally retrospective function; (b) anticipatory set (planning), which is a temporally prospective function; and (c) interference control (a form of attention that involves resistance to distraction), which inhibits the disruption of goal-directed behavior by events or behavior that are irrelevant to or incompatible with the goal. Fuster argues that the over-arching purpose of these three EF components is "the cross-temporal organization of behavior." (1997, p. 157) This is achieved by a temporal synthesis or integration that represents the "formation of temporal structures of behavior with a unifying purpose or goal – in other words, the structuring of goal-directed behavior." (p. 158) Like Stuss and Benson (1986), Fuster includes in his concept of EF the self-regulation of motivational, emotional, and other drive states in the service of goal-directed behavior.

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MoneyBrain – A.I. ChatBot Platform

The name hypothalamus means "under the thalamus". It forms the base of the third ventricle, an important reference point for the imaging of the brain. The hypothalamus is a complex, minute neural structure responsible for many aspects of behaviour such as basic biological drives, motivation and emotion. It is the link between the nervous and the neuroendocrine system, to be reviewed below. The pituitary gland (also called the hypophysis) is linked by neurons to the hypothalamic nuclei. It is well established that the hypothalamic nerve cells perform many neurosecretory functions. The hypothalamus is linked with many other major regions of the brain including the rhinencephalon-the primitive cortex originally associated with olfaction-and the limbic system, including the hippocampus.

The Lousy Linguist: syncing vs. synching

In this paper, we propose an emotional speech synthesis technique based on HMMs, especially for the case where only limited amount of training data is available, directly incorporating subjective evaluation results performed on the training data.

Natural-language processing - Wikipedia

Iida, Akemi; Campbell, Nick; Higuchi, Fumito, Yasumura, Michiaki 2003. A corpus-based speech synthesis system with emotion. Speech Communication 40, 161–187.

Dissertations & Theses from 2017

CIS 462 - Computer Animation
Prerequisite(s): Previous exposure to major concepts in linear algebra (i.e. vector matrix math), curves and surfaces, dynamical systems (e.g. 2nd order mass-spring-damper systems) and 3D computer graphics has also been assumed in the preparation of the course materials.

This course covers core subject matter common to the fields of robotics, character animation and embodied intelligent agents. The intent of the course is to provide the student with a solid technical foundation for developing, animating and controlling articulated systems used in interactive computer games, virtual reality simulations and high-end animation applications. The course balances theory with practice by "looking under the hood" of current animation systems and authoring tools and exams the technologies and techniques used from both a computer science and engineering perspective. Topics covered include: geometric coordinate systems and transformations; quaternions; parametric curves and surfaces; forward and inverse kinematics; dynamic systems and control; computer simulation; keyframe, motion capture and procedural animation; behavior-based animation and control; facial animation; smart characters and intelligent agents.

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