https://bitbucket.org/guokan_shang/abscomm
공식 코드Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding
Papers with Code 아카이브
Spoken Language Understanding
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://bitbucket.org/robvanderg/xsid
공식 코드https://github.com/193746/jsrsl
공식 코드Joint Automatic Speech Recognition And Structure Learning For Better Speech Understanding
https://github.com/AaronTengDeChuan/MLWA-Chinese-SLU
공식 코드Injecting Word Information with Multi-Level Word Adapter for Chinese Spoken Language Understanding
https://github.com/Adaxry/CM-Net
공식 코드CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding
https://github.com/Berkeley-Speech-Group/sylber
공식 코드Sylber: Syllabic Embedding Representation of Speech from Raw Audio
https://github.com/ColingPaper2018/DialogueAct-Tagger
공식 코드ISO-Standard Domain-Independent Dialogue Act Tagging for Conversational Agents
https://github.com/CoraJung/flexible-input-slu
공식 코드Speak or Chat with Me: End-to-End Spoken Language Understanding System with Flexible Inputs
https://github.com/F2-Song/PromptSLU
공식 코드A Unified Framework for Multi-intent Spoken Language Understanding with prompting
https://github.com/HPI-DeepLearning/crnn-lid
공식 코드Language Identification Using Deep Convolutional Recurrent Neural Networks
https://github.com/HarlinLee/brillsson
공식 코드Distilled Non-Semantic Speech Embeddings with Binary Neural Networks for Low-Resource Devices
https://github.com/Jiang-Yidi/TransformerDistillation-SLU
공식 코드Knowledge Distillation from BERT Transformer to Speech Transformer for Intent Classification
https://github.com/Kaleidophon/deep-significance
공식 코드https://github.com/LeePleased/StackPropagation-SLU
공식 코드A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding
https://github.com/Liang-Qiu/is13
공식 코드Recurrent Neural Networks with Pre-trained Language Model Embedding for Slot Filling Task
https://github.com/LooperXX/AGIF
공식 코드AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling
https://github.com/Magic-Ma-tech/Audio-Jailbreak-Attacks
공식 코드Audio Jailbreak Attacks: Exposing Vulnerabilities in SpeechGPT in a White-Box Framework
https://github.com/Microsoft/SDNet
공식 코드SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering
https://github.com/MiuLab/Lattice-ELMo
공식 코드Learning Spoken Language Representations with Neural Lattice Language Modeling
https://github.com/MiuLab/Lattice-SLU
공식 코드Learning Spoken Language Representations with Neural Lattice Language Modeling
https://github.com/MiuLab/SpokenVec
공식 코드Learning ASR-Robust Contextualized Embeddings for Spoken Language Understanding
https://github.com/MiuLab/Time-SLU
공식 코드Dynamic Time-Aware Attention to Speaker Roles and Contexts for Spoken Language Understanding
https://github.com/NVIDIA/NeMo
공식 코드https://github.com/OriShapira/ENDow
공식 코드Measuring the Effect of Transcription Noise on Downstream Language Understanding Tasks
https://github.com/Qatar-Computing-Research-Institute/dialectID
공식 코드https://github.com/SJY8460/SLM
공식 코드Do Large Language Model Understand Multi-Intent Spoken Language ?
https://github.com/Sanyuan-Chen/C2C-DA
공식 코드C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot Filling
https://github.com/Vernacular-ai/N-Best-ASR-Transformer
공식 코드N-Best ASR Transformer: Enhancing SLU Performance using Multiple ASR Hypotheses
https://github.com/aalto-speech/slurpfood
공식 코드Out-of-distribution generalisation in spoken language understanding
https://github.com/aarontengdechuan/pro-han
공식 코드Pro-HAN: A Heterogeneous Graph Attention Network for Profile-Based Spoken Language Understanding
https://github.com/afsara-ben/speechcache
공식 코드https://github.com/akreal/bloomzmms
공식 코드https://github.com/akshittyagi/intclass
공식 코드Fast Intent Classification for Spoken Language Understanding
https://github.com/ala-na/media_benchmark_intent_annotations
공식 코드New Semantic Task for the French Spoken Language Understanding MEDIA Benchmark
https://github.com/alanbaade/SyllableLM
공식 코드SyllableLM: Learning Coarse Semantic Units for Speech Language Models
https://github.com/alexa/alexa-dataset-contextual-query-rewrite
공식 코드A dataset for resolving referring expressions in spoken dialogue via contextual query rewrites (CQR)
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.