https://github.com/ms2ku-vtts/ms2ku-vtts
공식 코드Multi-Source Spatial Knowledge Understanding for Immersive Visual Text-to-Speech
Papers with Code 아카이브
Text to Speech
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import gTTS import os def text_to_speech_kurdish(text, output_file="output.mp3"): # گۆڕینی نووسین بۆ دەنگ بە زمانی کوردی (هەڵبژاردنی زمانی "ku" بۆ کوردی) tts = gTTS(text=text, lang='ku', slow=False) tts.save(output_file) os.system(f"start {output_file}") # کردنەوەی فایلە دەنگییەکە (لە Windows) # نموونە: text_to_speech_kurdish("سڵاو، ئەمە دەنگی منە بە زمانی کوردی.")
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/msalhab96/araspot
공식 코드https://github.com/mu-y/lll-tts
공식 코드Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis
https://github.com/mushanshanshan/esltts
공식 코드https://github.com/n8rob/multilingual_tts_augmentation
공식 코드https://github.com/natspeech/natspeech
공식 코드PortaSpeech: Portable and High-Quality Generative Text-to-Speech
https://github.com/naver-ai/RapFlow-TTS
공식 코드RapFlow-TTS: Rapid and High-Fidelity Text-to-Speech with Improved Consistency Flow Matching
https://github.com/naver-ai/facetts
공식 코드Imaginary Voice: Face-styled Diffusion Model for Text-to-Speech
https://github.com/naver-ai/usdm
공식 코드Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation
https://github.com/neonbjb/tortoise-tts
공식 코드https://github.com/neosapience/editts
공식 코드https://github.com/nethermanpro/transvip
공식 코드TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation
https://github.com/neubig/globalutility
공식 코드Systematic Inequalities in Language Technology Performance across the World's Languages
https://github.com/neulab/africanvoices
공식 코드https://github.com/neurowave-ai/cucvae-tts
공식 코드Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech
https://github.com/niger-volta-lti/yoruba-voice
공식 코드https://github.com/nii-yamagishilab/project-NN-Pytorch-scripts
공식 코드A Practical Guide to Logical Access Voice Presentation Attack Detection
https://github.com/nii-yamagishilab/self-attention-tacotron
공식 코드https://github.com/nsmq-ai/nsmqai
공식 코드Towards an AI to Win Ghana's National Science and Maths Quiz
https://github.com/ogunlao/glowtts_stdp
공식 코드Stochastic Pitch Prediction Improves the Diversity and Naturalness of Speech in Glow-TTS
https://github.com/open-mmlab/Amphion/blob/main/preprocessors/Emilia/README.md
공식 코드Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation
https://github.com/open-mmlab/amphion
공식 코드MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer
https://github.com/paarthneekhara/advoc
공식 코드https://github.com/papercup-open-source/phonological-features
공식 코드Phonological Features for 0-shot Multilingual Speech Synthesis
https://github.com/parthvshah/naturalization
공식 코드Naturalization of Text by the Insertion of Pauses and Filler Words
https://github.com/pedrodke/libris2s
공식 코드LibriS2S: A German-English Speech-to-Speech Translation Corpus
https://github.com/popcornell/ASRLightningFT
공식 코드Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech Recognition
https://github.com/pytorch/fairseq
공식 코드fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit
https://github.com/r9y9/wavenet_vocoder
공식 코드ESPnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit
https://github.com/rendchevi/nix-tts
공식 코드Nix-TTS: Lightweight and End-to-End Text-to-Speech via Module-wise Distillation
https://github.com/renqianluo/SemiNAS
공식 코드https://github.com/reseval/reseval
공식 코드https://github.com/roatienza/efficientspeech
공식 코드https://github.com/rohan-chaudhury/humane-speech-synthesis-through-zero-shot-emotion-and-disfluency-generation
공식 코드Humane Speech Synthesis through Zero-Shot Emotion and Disfluency Generation
https://github.com/roholazandie/ryan-tts
공식 코드RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis
https://github.com/rwsproat/text-normalization-data
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.