32,065 research outputs found
Emotion Generation using LPC Synthesis
S speech synthesis means artificial production of human speech . A system used for this purpose is called a speech synthesizer . The most important qualities of a speech synthesis system are naturalness and intelligibility . Naturalness describes how closely the output sounds like human speech, while intelligibility is the ease with which the ou tput is understood. Emotion is an important element in expressive speech synthesis. T his paper describes LPC analysis and synthesis technique . The LPC s are analyse d for each speech segmen t and pitch p eriod is detected . At synthesis the speech samples equal to the samples in one pitch period are reconstructed using LPC inverse synthesis. Thus by using LPC Synthesis we can implement pitch modification or duration modification or spectrum modification to introduce emotion in the neutral speech, such as happiness or anger
Learning Latent Representations for Speech Generation and Transformation
An ability to model a generative process and learn a latent representation
for speech in an unsupervised fashion will be crucial to process vast
quantities of unlabelled speech data. Recently, deep probabilistic generative
models such as Variational Autoencoders (VAEs) have achieved tremendous success
in modeling natural images. In this paper, we apply a convolutional VAE to
model the generative process of natural speech. We derive latent space
arithmetic operations to disentangle learned latent representations. We
demonstrate the capability of our model to modify the phonetic content or the
speaker identity for speech segments using the derived operations, without the
need for parallel supervisory data.Comment: Accepted to Interspeech 201
Toward Efficient Low Cost Highly Accurate Emotion Speech Synthesizer,
Abstract:
A Text to Speech (TTS) system with the ability to
express emotions is an interesting technology that is still
under development. There have been multiple proposals
to simulate emotion so far, and there are multiple
dimensions for assessment. No system guarantees high
score in all of these dimensions, this means that no
system works in a direction to get low computation load,
small database along with high accuracy and excellent
voice quality. After all of these qualities are relative and
fuzzy and there is no rigid grading system. In this paper
we will propose a new path for research that will work
toward improving all of the quality factors together, so
that future work can come up with a more optimum
solution for the emotional TTS systems
Teaching Language to Students with Autism
This meta-synthesis of the literature on methods of instruction to students with ASD examines the various methods of teaching language to students with ASD. While each student learns language at his or her own pace, the author has found that certain methods yield results quicker, and these methods need to be examined critically for any literature on their reliability, efficacy, and scientific research. If a student with autism can be taught language quickly, therefore mitigating any further delays in academic development relative to peers, then this methodology should be made accessible to all teachers of such students
Neural Dynamics of Autistic Behaviors: Cognitive, Emotional, and Timing Substrates
What brain mechanisms underlie autism and how do they give rise to autistic behavioral symptoms? This article describes a neural model, called the iSTART model, which proposes how cognitive, emotional, timing, and motor processes may interact together to create and perpetuate autistic symptoms. These model processes were originally developed to explain data concerning how the brain controls normal behaviors. The iSTART model shows how autistic behavioral symptoms may arise from prescribed breakdowns in these brain processes.Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624
Continuous Interaction with a Virtual Human
Attentive Speaking and Active Listening require that a Virtual Human be capable of simultaneous perception/interpretation and production of communicative behavior. A Virtual Human should be able to signal its attitude and attention while it is listening to its interaction partner, and be able to attend to its interaction partner while it is speaking – and modify its communicative behavior on-the-fly based on what it perceives from its partner. This report presents the results of a four week summer project that was part of eNTERFACE’10. The project resulted in progress on several aspects of continuous interaction such as scheduling and interrupting multimodal behavior, automatic classification of listener responses, generation of response eliciting behavior, and models for appropriate reactions to listener responses. A pilot user study was conducted with ten participants. In addition, the project yielded a number of deliverables that are released for public access
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