https://huggingface.co/naist-nlp/mitre_913m
공식 코드Registering Source Tokens to Target Language Spaces in Multilingual Neural Machine Translation
Papers with Code 아카이브
Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://zenodo.org/record/10500594
공식 코드https://bitbucket.org/ndnlp/speech2translation
An Unsupervised Probability Model for Speech-to-Translation Alignment of Low-Resource Languages
https://github.com/01pooja10/Sketch-to-Shoe
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/04RR/SOTA-Vision
https://github.com/0xSameer/ast
Pre-training on high-resource speech recognition improves low-resource speech-to-text translation
https://github.com/1-punchMan/CLTS
https://github.com/10-zin/Synthesizer
Synthesizer: Rethinking Self-Attention in Transformer Models
https://github.com/1230113202/NV-JM-DD
https://github.com/1alexandra/speech
Attention-Based Models for Text-Dependent Speaker Verification
https://github.com/1iyc/T2T-Analysis
https://github.com/1wy/bert
https://github.com/1ytic/warp-rnnt
https://github.com/201419/Optimizer-PyTorch
https://github.com/2023-MindSpore-1/ms-code-134
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-14/tree/main/GRU
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-14/tree/main/Transformer
https://github.com/2023-MindSpore-1/ms-code-149
https://github.com/2023-MindSpore-1/ms-code-158
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-169
https://github.com/2023-MindSpore-1/ms-code-184
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-197
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-200
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/dgcnet_res101
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/dnet_nas
D-Net: Siamese based Network with Mutual Attention for Volume Alignment
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/Pix2Pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/rfcn
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/siamRPN
SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/StarGAN
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/U-GAT-IT
https://github.com/2023-MindSpore-1/ms-code-5/tree/main/gnmt_v2
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/Pix2PixHD
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-61
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-62
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/U-GAT-IT
https://github.com/2023-MindSpore-1/ms-code-74
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.