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Text-To-Speech Synthesis
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Text-To-Speech Synthesis is a machine learning task that involves converting written text into spoken words. The goal is to generate synthetic speech that sounds natural and resembles human speech as closely as possible.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow Matching
S2ST-Omni: An Efficient and Scalable Multilingual Speech-to-Speech Translation Framework via Seamless Speech-Text Alignment and Streaming Speech Generation
A Novel Data Augmentation Approach for Automatic Speaking Assessment on Opinion Expressions
CapSpeech: Enabling Downstream Applications in Style-Captioned Text-to-Speech
SALF-MOS: Speaker Agnostic Latent Features Downsampled for MOS Prediction
Chain-of-Thought Training for Open E2E Spoken Dialogue Systems
Zero-Shot Streaming Text to Speech Synthesis with Transducer and Auto-Regressive Modeling
Revival with Voice: Multi-modal Controllable Text-to-Speech Synthesis
Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models
FMSD-TTS: Few-shot Multi-Speaker Multi-Dialect Text-to-Speech Synthesis for Ü-Tsang, Amdo and Kham Speech Dataset Generation
Shallow Flow Matching for Coarse-to-Fine Text-to-Speech Synthesis
Lightweight End-to-end Text-to-speech Synthesis for low resource on-device applications
A Multi-Agent Framework for Automated Qinqiang Opera Script Generation Using Large Language Models
AutoStyle-TTS: Retrieval-Augmented Generation based Automatic Style Matching Text-to-Speech Synthesis
Pseudo-Autoregressive Neural Codec Language Models for Efficient Zero-Shot Text-to-Speech Synthesis
MoonCast: High-Quality Zero-Shot Podcast Generation
ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech
VisualSpeech: Enhance Prosody with Visual Context in TTS
Low-Resource Text-to-Speech Synthesis Using Noise-Augmented Training of ForwardTacotron
PROEMO: Prompt-Driven Text-to-Speech Synthesis Based on Emotion and Intensity Control
Probing Speaker-specific Features in Speaker Representations
Stable-TTS: Stable Speaker-Adaptive Text-to-Speech Synthesis via Prosody Prompting
Incremental Disentanglement for Environment-Aware Zero-Shot Text-to-Speech Synthesis
ProsodyFM: Unsupervised Phrasing and Intonation Control for Intelligible Speech Synthesis
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
Multimodal Latent Language Modeling with Next-Token Diffusion
DiffStyleTTS: Diffusion-based Hierarchical Prosody Modeling for Text-to-Speech with Diverse and Controllable Styles
Debatts: Zero-Shot Debating Text-to-Speech Synthesis
Lina-Speech: Gated Linear Attention is a Fast and Parameter-Efficient Learner for text-to-speech synthesis
A Unified Framework for Collecting Text-to-Speech Synthesis Datasets for 22 Indian Languages
DurIAN-E 2: Duration Informed Attention Network with Adaptive Variational Autoencoder and Adversarial Learning for Expressive Text-to-Speech Synthesis
Bahasa Harmony: A Comprehensive Dataset for Bahasa Text-to-Speech Synthesis with Discrete Codec Modeling of EnGen-TTS
Efficient training strategies for natural sounding speech synthesis and speaker adaptation based on FastPitch
HALL-E: Hierarchical Neural Codec Language Model for Minute-Long Zero-Shot Text-to-Speech Synthesis
Generative Semantic Communication for Text-to-Speech Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.