https://github.com/SungFeng-Huang/Meta-TTS
공식 코드Meta-TTS: Meta-Learning for Few-Shot Speaker Adaptive Text-to-Speech
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Meta-TTS: Meta-Learning for Few-Shot Speaker Adaptive Text-to-Speech
One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech
SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and Synthesis
Towards Joint Modeling of Dialogue Response and Speech Synthesis based on Large Language Model
Using generative modelling to produce varied intonation for speech synthesis
Articulatory Phonetics Informed Controllable Expressive Speech Synthesis
FunCodec: A Fundamental, Reproducible and Integrable Open-source Toolkit for Neural Speech Codec
FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech Detection
Take the Hint: Improving Arabic Diacritization with Partially-Diacritized Text
Deep Speech Synthesis from MRI-Based Articulatory Representations
Fine-grained style control in Transformer-based Text-to-speech Synthesis
A Vector Quantized Approach for Text to Speech Synthesis on Real-World Spontaneous Speech
Visualising Model Training via Vowel Space for Text-To-Speech Systems
RFWave: Multi-band Rectified Flow for Audio Waveform Reconstruction
Independent and automatic evaluation of acoustic-to-articulatory inversion models
Self-Supervised Learning for Speech Enhancement through Synthesis
Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer Learning
From Speaker Verification to Multispeaker Speech Synthesis, Deep Transfer with Feedback Constraint
Time out of Mind: Generating Rate of Speech conditioned on emotion and speaker
Textless Unit-to-Unit training for Many-to-Many Multilingual Speech-to-Speech Translation
Retrieval-Augmented Dialogue Knowledge Aggregation for Expressive Conversational Speech Synthesis
Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.