https://github.com/is2ai/kazemotts
공식 코드KazEmoTTS: A Dataset for Kazakh Emotional Text-to-Speech Synthesis
Papers with Code 아카이브
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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/is2ai/turkictts
공식 코드Multilingual Text-to-Speech Synthesis for Turkic Languages Using Transliteration
https://github.com/jaywalnut310/glow-tts
공식 코드Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
https://github.com/jsalt-2022-ssl/superb-prosody
공식 코드On the Utility of Self-supervised Models for Prosody-related Tasks
https://github.com/justinlovelace/sesd
공식 코드https://github.com/jzq2000/mooncast
공식 코드https://github.com/k2-fsa/ZipVoice
공식 코드ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow Matching
https://github.com/kttrcdl/umetts
공식 코드UMETTS: A Unified Framework for Emotional Text-to-Speech Synthesis with Multimodal Prompts
https://github.com/lwang114/unsuptts
공식 코드Unsupervised Text-to-Speech Synthesis by Unsupervised Automatic Speech Recognition
https://github.com/marekkubis/bteval
공식 코드https://github.com/mbzuai-nlp/artst
공식 코드https://github.com/mbzuai-nlp/audiojailbreak
공식 코드Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models
https://github.com/microsoft/NeuralSpeech
공식 코드PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
https://github.com/microsoft/unilm
공식 코드Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/microsoft/unilm/tree/master/LatentLM
공식 코드Multimodal Latent Language Modeling with Next-Token Diffusion
https://github.com/mu-y/lll-tts
공식 코드Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis
https://github.com/natspeech/natspeech
공식 코드PortaSpeech: Portable and High-Quality Generative Text-to-Speech
https://github.com/naver-ai/facetts
공식 코드Imaginary Voice: Face-styled Diffusion Model for Text-to-Speech
https://github.com/neosapience/editts
공식 코드https://github.com/neubig/globalutility
공식 코드Systematic Inequalities in Language Technology Performance across the World's Languages
https://github.com/nii-yamagishilab/self-attention-tacotron
공식 코드https://github.com/numediart/EmoV-DB
공식 코드The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation Systems
https://github.com/ogunlao/glowtts_stdp
공식 코드Stochastic Pitch Prediction Improves the Diversity and Naturalness of Speech in Glow-TTS
https://github.com/roholazandie/ryan-tts
공식 코드RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis
https://github.com/sbu-dsl/prosody-analysis-of-audiobooks
공식 코드https://github.com/shark-nlp/attentivemlp
공식 코드Attentive Multi-Layer Perceptron for Non-autoregressive Generation
https://github.com/shinhyeokoh/rwen
공식 코드RWEN-TTS: Relation-aware Word Encoding Network for Natural Text-to-Speech Synthesis
https://github.com/shivammehta25/Matcha-TTS
공식 코드Matcha-TTS: A fast TTS architecture with conditional flow matching
https://github.com/shivammehta25/OverFlow
공식 코드OverFlow: Putting flows on top of neural transducers for better TTS
https://github.com/ssmlkl/mntts2
공식 코드MnTTS2: An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis Dataset
https://github.com/theodorblackbird/lina-speech
공식 코드https://github.com/tiberiu44/TTS-Cube
공식 코드https://github.com/walker-hyf/mntts
공식 코드MnTTS: An Open-Source Mongolian Text-to-Speech Synthesis Dataset and Accompanied Baseline
https://github.com/xiangli2022/cm-tts
공식 코드https://github.com/yl4579/StyleTTS
공식 코드StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech Synthesis
https://github.com/0fengzi0/tacotron
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.