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Voice Cloning

Voice cloning is a highly desired feature for personalized speech interfaces. Neural voice cloning system learns to synthesize a person’s voice from only a few audio samples.

Papers

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Showing 51–100 of 112 papers

TitleStatusHype
Pronunciation Deviation Analysis Through Voice Cloning and Acoustic Comparison—0
Real-time Detection of AI-Generated Speech for DeepFake Voice Conversion—0
Revisiting IPA-based Cross-lingual Text-to-speech—0
Scaling NVIDIA's Multi-speaker Multi-lingual TTS Systems with Zero-Shot TTS to Indic Languages—0
Securing Voice-driven Interfaces against Fake (Cloned) Audio Attacks—0
Self-supervised learning for robust voice cloning—0
Zero-Shot Long-Form Voice Cloning with Dynamic Convolution Attention—0
Voice Cloning for Dysarthric Speech Synthesis: Addressing Data Scarcity in Speech-Language Pathology—0
Adapting TTS models For New Speakers using Transfer Learning—0
Empowering Communication: Speech Technology for Indian and Western Accents through AI-powered Speech Synthesis—0
Advancing NAM-to-Speech Conversion with Novel Methods and the MultiNAM Dataset—0
Advancing Voice Cloning for Nepali: Leveraging Transfer Learning in a Low-Resource Language—0
AI based Presentation Creator With Customized Audio Content Delivery—0
Algorithms For Automatic Accentuation And Transcription Of Russian Texts In Speech Recognition Systems—0
A multi-speaker multi-lingual voice cloning system based on vits2 for limmits 2024 challenge—0
Augmentation through Laundering Attacks for Audio Spoof Detection—0
Beyond Face Swapping: A Diffusion-Based Digital Human Benchmark for Multimodal Deepfake Detection—0
Can DeepFake Speech be Reliably Detected?—0
CloneShield: A Framework for Universal Perturbation Against Zero-Shot Voice Cloning—0
Collaborative Watermarking for Adversarial Speech Synthesis—0
Cross-lingual Multi-speaker Text-to-speech Synthesis for Voice Cloning without Using Parallel Corpus for Unseen Speakers—0
CUHK-EE Voice Cloning System for ICASSP 2021 M2VoC Challenge—0
Data Efficient Voice Cloning for Neural Singing Synthesis—0
De-AntiFake: Rethinking the Protective Perturbations Against Voice Cloning Attacks—0
Deepfake Technology Unveiled: The Commoditization of AI and Its Impact on Digital Trust—0
DMOSpeech: Direct Metric Optimization via Distilled Diffusion Model in Zero-Shot Speech Synthesis—0
DubWise: Video-Guided Speech Duration Control in Multimodal LLM-based Text-to-Speech for Dubbing—0
Empowering Global Voices: A Data-Efficient, Phoneme-Tone Adaptive Approach to High-Fidelity Speech Synthesis—0
Towards Lightweight and Stable Zero-shot TTS with Self-distilled Representation Disentanglement—0
Translatotron 2: High-quality direct speech-to-speech translation with voice preservation—0
TRAVID: An End-to-End Video Translation Framework—0
Unsupervised TTS Acoustic Modeling for TTS with Conditional Disentangled Sequential VAE—0
V2C: Visual Voice Cloning—0
Voice Adaptation for Swiss German—0
VoiceCloak: A Multi-Dimensional Defense Framework against Unauthorized Diffusion-based Voice Cloning—0
Voice Cloning: a Multi-Speaker Text-to-Speech Synthesis Approach based on Transfer Learning—0
Voice Cloning: Comprehensive Survey—0
VoiceMark: Zero-Shot Voice Cloning-Resistant Watermarking Approach Leveraging Speaker-Specific Latents—0
Xiaomingbot: A Multilingual Robot News Reporter—0
a novel cross-lingual voice cloning approach with a few text-free samples—0
SoK: How Robust is Audio Watermarking in Generative AI models?—0
Speech Watermarking with Discrete Intermediate Representations—0
Spoken Language Corpora Augmentation with Domain-Specific Voice-Cloned Speech—0
kNN Retrieval for Simple and Effective Zero-Shot Multi-speaker Text-to-Speech—0
Steganography Beyond Space-Time with Chain of Multimodal AI—0
Taiwanese-Accented Mandarin and English Multi-Speaker Talking-Face Synthesis System—0
The AS-NU System for the M2VoC Challenge—0
The ISCSLP 2024 Conversational Voice Clone (CoVoC) Challenge: Tasks, Results and Findings—0
The Multi-speaker Multi-style Voice Cloning Challenge 2021—0
Learning Through AI-Clones: Enhancing Self-Perception and Presentation Performance—0
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