https://github.com/racai-ai/TEPROLIN
Tools and resources for Romanian text-to-speech and speech-to-text applications
Papers with Code 아카이브
Text-To-Speech Synthesis
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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/racai-ai/srla
Tools and resources for Romanian text-to-speech and speech-to-text applications
https://github.com/racai-ai/ssla
Tools and resources for Romanian text-to-speech and speech-to-text applications
https://github.com/racinmat/lecture-generator
https://github.com/revsic/tf-glow-tts
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
https://github.com/rhoposit/MOS_Estimation
https://github.com/rhoposit/MOS_Estimation2
https://github.com/rishikksh20/FastSpeech2
https://github.com/rishikksh20/LightSpeech
https://github.com/rishikksh20/iSTFTNet-pytorch
https://github.com/roedoejet/fastspeech2
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/roedoejet/fastspeech2_acl2022_reproducibility
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/rongjiehuang/transpeech
GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech
https://github.com/sam2125/translatotron
Direct speech-to-speech translation with a sequence-to-sequence model
https://github.com/serp-ai/bark-with-voice-clone
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/sewplay/demos
Effective parameter estimation methods for an ExcitNet model in generative text-to-speech systems
https://github.com/shivammehta25/BetterFastSpeech2
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/shortpoet/Final-Project
https://github.com/smoke-trees/Voice-synthesis
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
https://github.com/soobinseo/transformer-tts
https://github.com/suno-ai/bark
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/supertone-inc/super-monotonic-align
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
https://github.com/syang1993/gst-tacotron
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/tartunlp/transformertts
https://github.com/text-to-audio/make-an-audio
ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech
https://github.com/thethirdwheel/malumagraph
https://github.com/thuhcsi/tacotron
https://github.com/tigthor/Voice-Cloning-AI
https://github.com/tugstugi/pytorch-dc-tts
https://github.com/ung200/thats-what-obama-said
https://github.com/vardaan123/ParaNet
https://github.com/vohoaiviet/voice-vector
https://github.com/wataru-nakata/fastspeech2-jsut
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/xcmyz/FastSpeech
https://github.com/xinleiniu/latentoptimalpathsbayesiandp
RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis
https://github.com/yanggeng1995/EATS
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.