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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 Emotion Intensity and its Control for Emotional Voice Conversion ... Zhou, Kun; Sisman, Berrak; Rana, Rajib; Schuller, Björn W.; Li, Haizhou. - : arXiv, 2022 Abstract: Emotional voice conversion (EVC) seeks to convert the emotional state of an utterance while preserving the linguistic content and speaker identity. In EVC, emotions are usually treated as discrete categories overlooking the fact that speech also conveys emotions with various intensity levels that the listener can perceive. In this paper, we aim to explicitly characterize and control the intensity of emotion. We propose to disentangle the speaker style from linguistic content and encode the speaker style into a style embedding in a continuous space that forms the prototype of emotion embedding. We further learn the actual emotion encoder from an emotion-labelled database and study the use of relative attributes to represent fine-grained emotion intensity. To ensure emotional intelligibility, we incorporate emotion classification loss and emotion embedding similarity loss into the training of the EVC network. As desired, the proposed network controls the fine-grained emotion intensity in the output speech. ... : Submitted to IEEE Transactions on Affective Computing ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG; Sound cs.SD URL: https://arxiv.org/abs/2201.03967 https://dx.doi.org/10.48550/arxiv.2201.03967 BASE Hide details 2 Limited Data Emotional Voice Conversion Leveraging Text-to-Speech: Two-stage Sequence-to-Sequence Training ... Zhou, Kun; Sisman, Berrak; Li, Haizhou. - : arXiv, 2021 BASE Show details 3 Identity Conversion for Emotional Speakers: A Study for Disentanglement of Emotion Style and Speaker Identity ... Du, Zongyang; Sisman, Berrak; Zhou, Kun. - : arXiv, 2021 BASE Show details 4 An Overview of Voice Conversion and its Challenges: From Statistical Modeling to Deep Learning ... Sisman, Berrak; Yamagishi, Junichi; King, Simon. - : arXiv, 2020 BASE Show details 5 VAW-GAN for Disentanglement and Recomposition of Emotional Elements in Speech ... Zhou, Kun; Sisman, Berrak; Li, Haizhou. - : arXiv, 2020 BASE Show details 6 Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset ... Zhou, Kun; Sisman, Berrak; Liu, Rui. - : arXiv, 2020 BASE Show details 7 Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice Conversion ... Zhou, Kun; Sisman, Berrak; Zhang, Mingyang. - : arXiv, 2020 BASE Show details 8 Transforming Spectrum and Prosody for Emotional Voice Conversion with Non-Parallel Training Data ... Zhou, Kun; Sisman, Berrak; Li, Haizhou. - : arXiv, 2020 BASE Show details 9 VAW-GAN for Singing Voice Conversion with Non-parallel Training Data ... Lu, Junchen; Zhou, Kun; Sisman, Berrak. - : arXiv, 2020 BASE Show details 10 GraphSpeech: Syntax-Aware Graph Attention Network For Neural Speech Synthesis ... Liu, Rui; Sisman, Berrak; Li, Haizhou. - : arXiv, 2020 BASE Show details

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