An overview of voice conversion and its challenges: From statistical modeling to deep learning
Speaker identity is one of the important characteristics of human speech. In voice
conversion, we change the speaker identity from one to another, while keeping the linguistic …
conversion, we change the speaker identity from one to another, while keeping the linguistic …
Emotional voice conversion: Theory, databases and ESD
In this paper, we first provide a review of the state-of-the-art emotional voice conversion
research, and the existing emotional speech databases. We then motivate the development …
research, and the existing emotional speech databases. We then motivate the development …
Transforming spectrum and prosody for emotional voice conversion with non-parallel training data
Emotional voice conversion aims to convert the spectrum and prosody to change the
emotional patterns of speech, while preserving the speaker identity and linguistic content …
emotional patterns of speech, while preserving the speaker identity and linguistic content …
Transfer learning from speech synthesis to voice conversion with non-parallel training data
We present a novel voice conversion (VC) framework by learning from a text-to-speech
(TTS) synthesis system, that is called TTS-VC transfer learning or TTL-VC for short. We first …
(TTS) synthesis system, that is called TTS-VC transfer learning or TTL-VC for short. We first …
Cross-lingual voice conversion with bilingual phonetic posteriorgram and average modeling
This paper presents a cross-lingual voice conversion approach using bilingual Phonetic
PosteriorGram (PPG) and average modeling. The proposed approach makes use of …
PosteriorGram (PPG) and average modeling. The proposed approach makes use of …
Vaw-gan for disentanglement and recomposition of emotional elements in speech
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 study …
another while preserving the linguistic content and speaker identity. In this paper, we study …
Limited data emotional voice conversion leveraging text-to-speech: Two-stage sequence-to-sequence training
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 2 …
preserving the linguistic content and speaker identity. In this paper, we propose a novel 2 …
Unsupervised representation disentanglement using cross domain features and adversarial learning in variational autoencoder based voice conversion
An effective approach for voice conversion (VC) is to disentangle linguistic content from
other components in the speech signal. The effectiveness of variational autoencoder (VAE) …
other components in the speech signal. The effectiveness of variational autoencoder (VAE) …
SINGAN: Singing voice conversion with generative adversarial networks
Singing voice conversion (SVC) is a task to convert the source singer's voice to sound like
that of the target singer, without changing the lyrical content. So far, most of the voice …
that of the target singer, without changing the lyrical content. So far, most of the voice …
Semantically consistent text to fashion image synthesis with an enhanced attentional generative adversarial network
Abstract Recent advancements in Generative Adversarial Networks (GANs) have led to
significant improvements in various image generation tasks including image synthesis …
significant improvements in various image generation tasks including image synthesis …