Voice Cloning
17 papers with code • 0 benchmarks • 2 datasets
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.
Benchmarks
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Libraries
Use these libraries to find Voice Cloning models and implementations
GneutralSpeech Female
Most implemented papers
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
CorentinJ/Real-Time-Voice-Cloning
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NeurIPS 2018
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning
We present a multispeaker, multilingual text-to-speech (TTS) synthesis model based on Tacotron that is able to produce high quality speech in multiple languages.
Neural Voice Cloning with a Few Samples
jackaduma/CycleGAN-VC2
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NeurIPS 2018
Speaker adaptation is based on fine-tuning a multi-speaker generative model with a few cloning samples.
ERNIE-SAT: Speech and Text Joint Pretraining for Cross-Lingual Multi-Speaker Text-to-Speech
In this paper, we extend the pretraining method for cross-lingual multi-speaker speech synthesis tasks, including cross-lingual multi-speaker voice cloning and cross-lingual multi-speaker speech editing.
Enhancing Suno's Bark Text-to-Speech Model: Addressing Limitations Through Meta's Encodec and Pre-Trained Hubert
serp-ai/bark-with-voice-clone
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Social Science Research Network (SSRN) 2023
Keywords: Bark, ai voice cloning, Suno, text-to-speech, artificial intelligence, audio generation, Meta's encodec, audio codebooks, semantic tokens, HuBert, transformer-based model, multilingual speech, wav2vec, linear projection head, embedding space, generative capabilities, pretrained model checkpoints
Anonymizing Speech: Evaluating and Designing Speaker Anonymization Techniques
The growing use of voice user interfaces has led to a surge in the collection and storage of speech data.
One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech
Tomiinek/Multilingual_Text_to_Speech
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We introduce an approach to multilingual speech synthesis which uses the meta-learning concept of contextual parameter generation and produces natural-sounding multilingual speech using more languages and less training data than previous approaches.
Investigating on Incorporating Pretrained and Learnable Speaker Representations for Multi-Speaker Multi-Style Text-to-Speech
The few-shot multi-speaker multi-style voice cloning task is to synthesize utterances with voice and speaking style similar to a reference speaker given only a few reference samples.
Building Bilingual and Code-Switched Voice Conversion with Limited Training Data Using Embedding Consistency Loss
We achieve cross-lingual VC between Mandarin speech with multiple speakers and English speech with multiple speakers by applying bilingual bottleneck features.
Txt2Vid: Ultra-Low Bitrate Compression of Talking-Head Videos via Text
tpulkit/txt2vid
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Video represents the majority of internet traffic today, driving a continual race between the generation of higher quality content, transmission of larger file sizes, and the development of network infrastructure.
