Papers with Code 아카이브

Speech Emotion Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/R00Kie-Liu/TA2N

공식 코드

TA2N: Two-Stage Action Alignment Network for Few-shot Action Recognition

https://github.com/RQ-Wu/RIDCP_dehazing

공식 코드

RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors

https://github.com/Raminghorbanii/Self-Supervised-PPG-Representation-Learning-Shows-High-Inter-Subject-Variability

공식 코드

Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability

https://github.com/RaymZhang/TS_Combinatorial_Semi_Bandits_Curse

공식 코드

On the Suboptimality of Thompson Sampling in High Dimensions

https://github.com/Rhitabrat/youtube-comments-categorization

공식 코드

Classifying YouTube Comments Based on Sentiment and Type of Sentence

https://github.com/RichardMoot/GrailLight

공식 코드

The Grail theorem prover: Type theory for syntax and semantics

https://github.com/RixonC/DINGO

공식 코드

DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization

https://github.com/Rongjiehuang/FastDiff

공식 코드

FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis

https://github.com/Rongjiehuang/ProDiff

공식 코드

ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech

https://github.com/RuiLiFeng/Deep-Generative-Projection

공식 코드

Weakly Supervised High-Fidelity Clothing Model Generation

https://github.com/SCCAF/sccaf

공식 코드

Putative cell type discovery from single-cell gene expression data

https://github.com/SPEECHCOG/cpc_pytorch

공식 코드

Analysis of Self-Supervised Learning and Dimensionality Reduction Methods in Clustering-Based Active Learning for Speech Emotion Recognition

https://github.com/Safe-DS/DSL

공식 코드

Safe-DS: A Domain Specific Language to Make Data Science Safe

https://github.com/Salingo/CTF-Net

공식 코드

Consistent Two-Flow Network for Tele-Registration of Point Clouds

https://github.com/SaschaHornauer/Batvision

공식 코드

BatVision: Learning to See 3D Spatial Layout with Two Ears

https://github.com/ShangtongZhang/DeepRL

공식 코드

Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation

https://github.com/ShinyWang33/eSL-Net

공식 코드

Event Enhanced High-Quality Image Recovery

https://github.com/ShuyangCao/open-ended_question_ontology

공식 코드

Controllable Open-ended Question Generation with A New Question Type Ontology

https://github.com/SkBlaz/PropStar

공식 코드

Propositionalization and Embeddings: Two Sides of the Same Coin

https://github.com/SkBlaz/reliefe

공식 코드

ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings

https://github.com/SocratesNFR/Evolving-spiking-neuron-cellular-automata-and-networks-to-emulate-in-vitro-neuronal-activity

공식 코드

Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity

https://github.com/SoumiDas/HOST-CP

공식 코드

Finding High-Value Training Data Subset through Differentiable Convex Programming

https://github.com/Soumyabrata/HDR-cloud-segmentation

공식 코드

High-Dynamic-Range Imaging for Cloud Segmentation

https://github.com/SparseGridsForDynamicEcon/HDMR

공식 코드

High-Dimensional Dynamic Stochastic Model Representation

https://github.com/Spencerfar/djin-aging

공식 코드

Interpretable machine learning for high-dimensional trajectories of aging health

https://github.com/Stalence/NeuralExt

공식 코드

Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions

https://github.com/Stefan-Pasch/CultureBERT

공식 코드

CultureBERT: Measuring Corporate Culture With Transformer-Based Language Models

https://github.com/SysCV/transfiner

공식 코드

Mask Transfiner for High-Quality Instance Segmentation

https://github.com/TIBHannover/VisE

공식 코드

Ontology-driven Event Type Classification in Images

https://github.com/TLouf/words-use

공식 코드

American cultural regions mapped through the lexical analysis of social media

https://github.com/TUM-AIMED/MoNet

공식 코드

Efficient, high-performance pancreatic segmentation using multi-scale feature extraction

https://github.com/TUM-LMF/BreizhCrops

공식 코드

BreizhCrops: A Time Series Dataset for Crop Type Mapping

https://github.com/TamirBendory/high-dimensional-mra-bounds

공식 코드

Multi-reference alignment in high dimensions: sample complexity and phase transition

https://github.com/Tengfei-Wang/HFGI

공식 코드

High-Fidelity GAN Inversion for Image Attribute Editing

https://github.com/Tju-AI/two-stage-labeling-for-the-sentiment-orientations

공식 코드

$ρ$-hot Lexicon Embedding-based Two-level LSTM for Sentiment Analysis

https://github.com/TobiasGruening/ARU-Net

공식 코드

A Two-Stage Method for Text Line Detection in Historical Documents

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.