21 citations · 31 across the 5 of their papers we have counts for
10 papers
Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals
Yutao Zhu, Jian-Yun Nie, Kun Zhou +3
A proactive dialogue system has the ability to proactively lead the conversation. Different from the general chatbots which only react to the user, proactive dialogue systems can b…
Expressive Voice Conversion: A Joint Framework for Speaker Identity and Emotional Style Transfer
Zongyang Du, Berrak Sisman, Kun Zhou +1
Traditional voice conversion(VC) has been focused on speaker identity conversion for speech with a neutral expression. We note that emotional expression plays an essential role in…
Limited Data Emotional Voice Conversion Leveraging Text-to-Speech: Two-stage Sequence-to-Sequence Training
Kun Zhou, Berrak Sisman, Haizhou Li
Emotional voice conversion (EVC) aims to change the emotional state of an utterance while preserving the linguistic content and speaker identity. In this paper, we propose a novel…
Content Selection Network for Document-grounded Retrieval-based Chatbots
Yutao Zhu, Jian-Yun Nie, Kun Zhou +2
Grounding human-machine conversation in a document is an effective way to improve the performance of retrieval-based chatbots. However, only a part of the document content may be r…
VAW-GAN for Disentanglement and Recomposition of Emotional Elements in Speech
Kun Zhou, Berrak Sisman, Haizhou Li
Emotional voice conversion (EVC) aims to convert the emotion of speech from one state to another while preserving the linguistic content and speaker identity. In this paper, we stu…
Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset
Kun Zhou, Berrak Sisman, Rui Liu +1
Emotional voice conversion aims to transform emotional prosody in speech while preserving the linguistic content and speaker identity. Prior studies show that it is possible to dis…