https://github.com/Tomiinek/Multilingual_Text_to_Speech
공식 코드One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech
Papers with Code 아카이브
Speech Synthesis
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 15
- 평가표
- 5
- 보존된 평가 기록
- 31
Speech synthesis is the task of generating speech from some other modality like text, lip movements etc.
Please note that the leaderboards here are not really comparable between studies - as they use mean opinion score as a metric and collect different samples from Amazon Mechnical Turk.
<span style="color:grey; opacity: 0.6">( Image credit: WaveNet: A generative model for raw audio )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/WangHelin1997/SSR-Speech
공식 코드SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and Synthesis
https://github.com/XiaoyuBIE1994/DVAE
공식 코드https://github.com/XinyuZhou2000/Spoken_Dialogue
공식 코드Towards Joint Modeling of Dialogue Response and Speech Synthesis based on Large Language Model
https://github.com/ZackHodari/average_prosody
공식 코드Using generative modelling to produce varied intonation for speech synthesis
https://github.com/ZackHodari/discrete_intonation
공식 코드https://github.com/ZehuaKcrissLi/GTR-Voice
공식 코드Articulatory Phonetics Informed Controllable Expressive Speech Synthesis
https://github.com/ai-s2-lab/gpt-talker
공식 코드https://github.com/alibaba-damo-academy/funcodec
공식 코드FunCodec: A Fundamental, Reproducible and Integrable Open-source Toolkit for Neural Speech Codec
https://github.com/amforever/fmfcc-a
공식 코드FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech Detection
https://github.com/apple/dmel
공식 코드https://github.com/apptek/arabicdiacritizationinterspeech2023
공식 코드Take the Hint: Improving Arabic Diacritization with Partially-Diacritized Text
https://github.com/articulatory/articulatory
공식 코드Deep Speech Synthesis from MRI-Based Articulatory Representations
https://github.com/b04901014/FG-transformer-TTS
공식 코드Fine-grained style control in Transformer-based Text-to-speech Synthesis
https://github.com/b04901014/mqtts
공식 코드A Vector Quantized Approach for Text to Speech Synthesis on Real-World Spontaneous Speech
https://github.com/babe269/performant
공식 코드Visualising Model Training via Vowel Space for Text-To-Speech Systems
https://github.com/bfs18/rfwave
공식 코드RFWave: Multi-band Rectified Flow for Audio Waveform Reconstruction
https://github.com/bfs18/tacotron2
공식 코드https://github.com/bootphon/articulatory_inversion
공식 코드Independent and automatic evaluation of acoustic-to-articulatory inversion models
https://github.com/bosecorp/devo
공식 코드Self-Supervised Learning for Speech Enhancement through Synthesis
https://github.com/c3imaging/child_tts_fastpitch
공식 코드Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer Learning
https://github.com/caizexin/tf_multispeakerTTS_fc
공식 코드From Speaker Verification to Multispeaker Speech Synthesis, Deep Transfer with Feedback Constraint
https://github.com/candlewill/RawNet
공식 코드https://github.com/chocobearz/speech_timing
공식 코드Time out of Mind: Generating Rate of Speech conditioned on emotion and speaker
https://github.com/choijeongsoo/lip2speech-unit
공식 코드https://github.com/choijeongsoo/utut
공식 코드Textless Unit-to-Unit training for Many-to-Many Multilingual Speech-to-Speech Translation
https://github.com/chris10m/lip2speech
공식 코드https://github.com/cnaigithub/Auto_Tuning_Zeroshot_TTS_and_VC
공식 코드https://github.com/coder-jzq/radka-css
공식 코드Retrieval-Augmented Dialogue Knowledge Aggregation for Expressive Conversational Speech Synthesis
https://github.com/collectivat-dev/espanyol-ladino-translation
공식 코드Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
https://github.com/collectivat-dev/judeo-espanyol-resources
공식 코드Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
https://github.com/collectivat-dev/ladino_tts
공식 코드Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish
https://github.com/coqui-ai/TTS
공식 코드YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone
https://github.com/cyanbx/FastLTS
공식 코드FastLTS: Non-Autoregressive End-to-End Unconstrained Lip-to-Speech Synthesis
https://github.com/cyjie429/rego
공식 코드Region-Based Optimization in Continual Learning for Audio Deepfake Detection
https://github.com/d223302/subjectiveevaluation
공식 코드Why We Should Report the Details in Subjective Evaluation of TTS More Rigorously
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.