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Papers by GOKCE IYMEN
arXiv (Cornell University), Oct 6, 2022
Speech is the fundamental mode of human communication, and its synthesis has long been a core pri... more Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research. In recent years, machines have managed to master the art of generating speech that is understandable by humans. But the linguistic content of an utterance encompasses only a part of its meaning. Affect, or expressivity, has the capacity to turn speech into a medium capable of conveying intimate thoughts, feelings, and emotionsaspects that are essential for engaging and naturalistic interpersonal communication. While the goal of imparting expressivity to synthesised utterances has so far remained elusive, following recent advances in text-to-speech synthesis, a paradigm shift is well under way in the fields of affective speech synthesis and conversion as well. Deep learning, as the technology which underlies most of the recent advances in artificial intelligence, is spearheading these efforts. In the present overview, we outline ongoing trends and summarise state-of-the-art approaches in an attempt to provide a comprehensive overview of this exciting field.
Proceedings of the IEEE
Speech is the fundamental mode of human communication, and its synthesis has long been a core pri... more Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research. In recent years, machines have managed to master the art of generating speech that is understandable by humans. But the linguistic content of an utterance encompasses only a part of its meaning. Affect, or expressivity, has the capacity to turn speech into a medium capable of conveying intimate thoughts, feelings, and emotionsaspects that are essential for engaging and naturalistic interpersonal communication. While the goal of imparting expressivity to synthesised utterances has so far remained elusive, following recent advances in text-to-speech synthesis, a paradigm shift is well under way in the fields of affective speech synthesis and conversion as well. Deep learning, as the technology which underlies most of the recent advances in artificial intelligence, is spearheading these efforts. In the present overview, we outline ongoing trends and summarise state-of-the-art approaches in an attempt to provide a comprehensive overview of this exciting field.
COJ Robotics & Artificial Intelligence, Aug 6, 2020
Generative adversarial networks have become increasingly popular since they were first introduced... more Generative adversarial networks have become increasingly popular since they were first introduced in 2014. Many variants of GANs have been developed over the years and employed in a range of applications from computer vision to audio generation and medical imaging. As its applications in computer vision have been widely explored by the artificial intelligence community, here, we focus on more specific applications of GANs, namely audio generation and medical image synthesis. In the age of big data, these two fields still struggle with the scarcity of labelled data, hence they benefit greatly from the capabilities of GANs.
Innovative Food Science & Emerging Technologies
arXiv (Cornell University), Oct 6, 2022
Speech is the fundamental mode of human communication, and its synthesis has long been a core pri... more Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research. In recent years, machines have managed to master the art of generating speech that is understandable by humans. But the linguistic content of an utterance encompasses only a part of its meaning. Affect, or expressivity, has the capacity to turn speech into a medium capable of conveying intimate thoughts, feelings, and emotionsaspects that are essential for engaging and naturalistic interpersonal communication. While the goal of imparting expressivity to synthesised utterances has so far remained elusive, following recent advances in text-to-speech synthesis, a paradigm shift is well under way in the fields of affective speech synthesis and conversion as well. Deep learning, as the technology which underlies most of the recent advances in artificial intelligence, is spearheading these efforts. In the present overview, we outline ongoing trends and summarise state-of-the-art approaches in an attempt to provide a comprehensive overview of this exciting field.
Proceedings of the IEEE
Speech is the fundamental mode of human communication, and its synthesis has long been a core pri... more Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research. In recent years, machines have managed to master the art of generating speech that is understandable by humans. But the linguistic content of an utterance encompasses only a part of its meaning. Affect, or expressivity, has the capacity to turn speech into a medium capable of conveying intimate thoughts, feelings, and emotionsaspects that are essential for engaging and naturalistic interpersonal communication. While the goal of imparting expressivity to synthesised utterances has so far remained elusive, following recent advances in text-to-speech synthesis, a paradigm shift is well under way in the fields of affective speech synthesis and conversion as well. Deep learning, as the technology which underlies most of the recent advances in artificial intelligence, is spearheading these efforts. In the present overview, we outline ongoing trends and summarise state-of-the-art approaches in an attempt to provide a comprehensive overview of this exciting field.
COJ Robotics & Artificial Intelligence, Aug 6, 2020
Generative adversarial networks have become increasingly popular since they were first introduced... more Generative adversarial networks have become increasingly popular since they were first introduced in 2014. Many variants of GANs have been developed over the years and employed in a range of applications from computer vision to audio generation and medical imaging. As its applications in computer vision have been widely explored by the artificial intelligence community, here, we focus on more specific applications of GANs, namely audio generation and medical image synthesis. In the age of big data, these two fields still struggle with the scarcity of labelled data, hence they benefit greatly from the capabilities of GANs.
Innovative Food Science & Emerging Technologies