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Speech Emotion Recognition

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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://bitbucket.org/AnatoliyBabic/swi-scisports-2018

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SciSports: Learning football kinematics through two-dimensional tracking data

https://bitbucket.org/chhshen/fasthash

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Fast Supervised Hashing with Decision Trees for High-Dimensional Data

https://bitbucket.org/uwtppml/idash2019

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High Performance Logistic Regression for Privacy-Preserving Genome Analysis

https://bitbucket.org/wtstephe/sparse_appx_cv

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Approximate Cross-Validation in High Dimensions with Guarantees

https://git.noc.ruhr-uni-bochum.de/vepabm/invano-public

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The effects of incentives, social norms, and employees' values on work performance

https://git.skewed.de/count0/graph-tool

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Hierarchical Block Structures and High-resolution Model Selection in Large Networks

https://github.com/1Konny/idgan

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High-Fidelity Synthesis with Disentangled Representation

https://github.com/1adrianb/expert-binary-networks

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High-Capacity Expert Binary Networks

https://github.com/601175936/homi

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Multi-label Classification with High-rank and High-order Label Correlations

https://github.com/95anantsingh/decoding-emotions

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Decoding Emotions: A comprehensive Multilingual Study of Speech Models for Speech Emotion Recognition

https://github.com/AClon42/two-sample-anisotropic

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Two-sample Statistics Based on Anisotropic Kernels

https://github.com/AI-Unicamp/interspeech_ser

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Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking Model

https://github.com/AMICI-dev/AMICI

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AMICI: High-Performance Sensitivity Analysis for Large Ordinary Differential Equation Models

https://github.com/ANTsX/ANTsR

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Interpretable, similarity-driven multi-view embeddings from high-dimensional biomedical data

https://github.com/ARBML/Calliar

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Calliar: An Online Handwritten Dataset for Arabic Calligraphy

https://github.com/ATriantafyllopoulos/enrollment-personalization

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Enrolment-based personalisation for improving individual-level fairness in speech emotion recognition

https://github.com/ATriantafyllopoulos/is24-interspeech09-ser-revisited

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INTERSPEECH 2009 Emotion Challenge Revisited: Benchmarking 15 Years of Progress in Speech Emotion Recognition

https://github.com/Adam1679/ConnectE

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Connecting Embeddings for Knowledge Graph Entity Typing

https://github.com/AlanZhang1995/TwoStreamSR

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Two-Stream Action Recognition-Oriented Video Super-Resolution

https://github.com/Alibaba-MIIL/CobBO

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CobBO: Coordinate Backoff Bayesian Optimization with Two-Stage Kernels

https://github.com/AmirSh15/Compact_SER

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Compact Graph Architecture for Speech Emotion Recognition

https://github.com/AmirSh15/SSL_graph_audio

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Self-supervised Graphs for Audio Representation Learning with Limited Labeled Data

https://github.com/Atlas200dk/sample-imageinpainting-HiFill

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Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting

https://github.com/BIDData/BIDMach

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SAME but Different: Fast and High-Quality Gibbs Parameter Estimation

https://github.com/BUGPLEASEOUT/LasHeR

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LasHeR: A Large-scale High-diversity Benchmark for RGBT Tracking

https://github.com/BUTSpeechFIT/BrnoLM

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Text Augmentation for Language Models in High Error Recognition Scenario

https://github.com/BaratiLab/Diffusion-based-Fluid-Super-resolution

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A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction

https://github.com/BeautyOfWeb/AffinityNet

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AffinityNet: semi-supervised few-shot learning for disease type prediction

https://github.com/BenoitWang/Speech_Emotion_Diarization

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Speech Emotion Diarization: Which Emotion Appears When?

https://github.com/BestActionNow/SemiSupBLI

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Semi-Supervised Bilingual Lexicon Induction with Two-way Interaction

https://github.com/BorealisAI/mtmfrl

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Multi Type Mean Field Reinforcement Learning

https://github.com/BoyanJIANG/LoRD

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LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling

https://github.com/CEA-LIST/AD-RobustnessEval

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Evaluating Robustness over High Level Driving Instruction for Autonomous Driving

https://github.com/CHNPAT005/PCIJAPTG-A2XvsJSE

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Comparing the market microstructure between two South African exchanges

https://github.com/CIFASIS/exploiting-gan-internal-capacity

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Exploiting GAN Internal Capacity for High-Quality Reconstruction of Natural Images

https://github.com/CVMI-Lab/UHDM

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Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing

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