https://github.com/M4t1ss/sentiment-analysis-toolkit
공식 코드Fragmented and Valuable: Following Sentiment Changes in Food Tweets
Papers with Code 아카이브
Speech Emotion Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 17
- 보존된 평가 기록
- 48
Speech Emotion Recognition is a task of speech processing and computational paralinguistics that aims to recognize and categorize the emotions expressed in spoken language. The goal is to determine the emotional state of a speaker, such as happiness, anger, sadness, or frustration, from their speech patterns, such as prosody, pitch, and rhythm.
For multimodal emotion recognition, please upload your result to Multimodal Emotion Recognition on IEMOCAP
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MartinPernus/MaskFaceGAN
공식 코드High Resolution Face Editing with Masked GAN Latent Code Optimization
https://github.com/MarvinLvn/voice-type-classifier
공식 코드An open-source voice type classifier for child-centered daylong recordings
https://github.com/MatanCohen1/Transformaly
공식 코드https://github.com/Mathux/FROT
공식 코드https://github.com/Microsoft/human-pose-estimation.pytorch
공식 코드Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/MihawkHu/DCASE2020_task1
공식 코드A Two-Stage Approach to Device-Robust Acoustic Scene Classification
https://github.com/MrVPlusOne/LambdaNet
공식 코드LambdaNet: Probabilistic Type Inference using Graph Neural Networks
https://github.com/MungoMeng/Panorama-OpticalFlow
공식 코드High-quality Panorama Stitching based on Asymmetric Bidirectional Optical Flow
https://github.com/MungoMeng/Spiking-Inception
공식 코드High-parallelism Inception-like Spiking Neural Networks for Unsupervised Feature Learning
https://github.com/NFFT/ANOVAapprox
공식 코드https://github.com/NFFT/AttributeRankingExamples
공식 코드https://github.com/NVIDIA/pix2pixHD
공식 코드High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/NVlabs/nvdiffrast
공식 코드Modular Primitives for High-Performance Differentiable Rendering
https://github.com/NVlabs/two-shot-brdf-shape
공식 코드https://github.com/Nakols/HFformerV2
공식 코드Exploring the Advantages of Transformers for High-Frequency Trading
https://github.com/NeurEXT/NEXT-learning-to-plan/blob/master/main.ipynb
공식 코드Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees
https://github.com/NiMlr/High-Dim-ES-RL
공식 코드Challenges in High-dimensional Reinforcement Learning with Evolution Strategies
https://github.com/NiallJeffrey/MomentNetworks
공식 코드Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks
https://github.com/NoemieJaquier/GaBOtorch
공식 코드High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds
https://github.com/OSU-CMR/HICU
공식 코드High-dimensional Fast Convolutional Framework (HICU) for Calibrationless MRI
https://github.com/OmarHagrass/Spectral-regularized-two-sample-test
공식 코드https://github.com/OmarMohammed88/AR-Emotion-Recognition
공식 코드Arabic Speech Emotion Recognition Employing Wav2vec2.0 and HuBERT Based on BAVED Dataset
https://github.com/P2333/Rectified-Rejection
공식 코드Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart
https://github.com/PaddlePaddle/PaddleSeg
공식 코드PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation
https://github.com/PaddlePaddle/models
공식 코드Towards Conversational Recommendation over Multi-Type Dialogs
https://github.com/Panern/HMvC
공식 코드https://github.com/Pea-Shooter/ADNet
공식 코드ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/PeterL1n/BackgroundMattingV2
공식 코드https://github.com/PeterL1n/RobustVideoMatting
공식 코드https://github.com/PierreMarion23/two-timescale-nn
공식 코드Leveraging the two timescale regime to demonstrate convergence of neural networks
https://github.com/PouyaREZ/GAN_GA
공식 코드Augmenting High-dimensional Nonlinear Optimization with Conditional GANs
https://github.com/Pythongoras/ConeProjectedPowerIter
공식 코드Non-Sparse PCA in High Dimensions via Cone Projected Power Iteration
https://github.com/QB3/sparse-ho
공식 코드Implicit differentiation of Lasso-type models for hyperparameter optimization
https://github.com/Qsingle/MegVision
공식 코드SuperVessel: Segmenting High-resolution Vessel from Low-resolution Retinal Image
https://github.com/QuantLet/CCID
공식 코드Rise of the Machines? Intraday High-Frequency Trading Patterns of Cryptocurrencies
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.