https://github.com/MiuLab/HNLG
공식 코드Natural Language Generation by Hierarchical Decoding with Linguistic Patterns
Papers with Code 아카이브
Spoken Dialogue Systems
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/PolyAI-LDN/evi-paper
공식 코드https://github.com/UFAL-DSG/tgen
공식 코드A Context-aware Natural Language Generator for Dialogue Systems
https://github.com/X-LANCE/SLAM-LLM
공식 코드SLAM-Omni: Timbre-Controllable Voice Interaction System with Single-Stage Training
https://github.com/XinyuZhou2000/Spoken_Dialogue
공식 코드Towards Joint Modeling of Dialogue Response and Speech Synthesis based on Large Language Model
https://github.com/alexa/alexa-dataset-contextual-query-rewrite
공식 코드A dataset for resolving referring expressions in spoken dialogue via contextual query rewrites (CQR)
https://github.com/eleutherai/gpt-neox
공식 코드PSLM: Parallel Generation of Text and Speech with LLMs for Low-Latency Spoken Dialogue Systems
https://github.com/jishengpeng/wavchat
공식 코드https://github.com/jishengpeng/wavreward
공식 코드WavReward: Spoken Dialogue Models With Generalist Reward Evaluators
https://github.com/karpathy/nanogpt
공식 코드OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation
https://github.com/mailong25/rts2s-dg
공식 코드https://github.com/orange-opensource/olisia-dstc11
공식 코드https://github.com/sarulab-speech/saslaw
공식 코드https://github.com/siyan-sylvia-li/icarus_final
공식 코드When can I Speak? Predicting initiation points for spoken dialogue agents
https://github.com/uber-research/plato-research-dialogue-system
공식 코드Plato Dialogue System: A Flexible Conversational AI Research Platform
https://bitbucket.org/skeizer/madrigal
Towards Learning Transferable Conversational Skills using Multi-dimensional Dialogue Modelling
https://github.com/HarshitaSahai/conversational-agent
Plato Dialogue System: A Flexible Conversational AI Research Platform
https://github.com/RasaHQ/rasa
https://github.com/alexa/alexa-with-dstc10-track2-dataset
"How Robust r u?": Evaluating Task-Oriented Dialogue Systems on Spoken Conversations
https://github.com/andy194673/nlg-sclstm-multiwoz
Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems
https://github.com/andy194673/nlg-scvae
Variational Cross-domain Natural Language Generation for Spoken Dialogue Systems
https://github.com/istar1978/plato
Plato Dialogue System: A Flexible Conversational AI Research Platform
https://github.com/kolk/MODELING-ASR-AMBIGUITY-FOR-NEURAL-DIALOGUE-STATE-TRACKING-USING-WORD-CONFUSION-NETWORKS
Modeling ASR Ambiguity for Dialogue State Tracking Using Word Confusion Networks
https://github.com/mrcmoresi/sc-lstm
Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems
https://github.com/uber-archive/plato-research-dialogue-system
Plato Dialogue System: A Flexible Conversational AI Research Platform
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.