Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: AVEC 2015: The 5th International Audio/Visual Emotion Challenge and Workshop
AV+EC 2015: The First Affect Recognition Challenge Bridging Across Audio, Video, and Physiological Data
Semantic audio-visual data fusion for automatic emotion recognition
The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English
Video Affective Content Analysis: A Survey of State-of-the-Art Methods
AVEC 2016: Depression, Mood, and Emotion Recognition Workshop and Challenge
Audio-Visual Emotion Recognition Using Gaussian Mixture Models for Face and Voice
Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge
Audio-visual feature selection and reduction for emotion classification
Audio-Visual Sentiment Analysis for Learning Emotional Arcs in Movies
Emotion elicitation using films
EmoNets: Multimodal deep learning approaches for emotion recognition in video
Multimodal Emotion Recognition in Videos
Deep learning for robust feature generation in audiovisual emotion recognition
At the Border of Acoustics and Linguistics: Bag-of-Audio-Words for the Recognition of Emotions in Speech.
Automatic Speech Emotion Recognition: A survey
the interspeech 2009 emotion challenge .
Acoustic emotion recognition: A benchmark comparison of performances
MEC 2016: The Multimodal Emotion Recognition Challenge of CCPR 2016
Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data
Multimodal Emotion Recognition in Response to Videos
An Ontological Model for Fire Emergency Situations
Improving Multi-label Learning with Missing Labels by Structured Semantic Correlations
Collecting Large, Richly Annotated Facial-Expression Databases from Movies
Rhamnolipids and lactonic sophorolipids: natural antimicrobial surfactants for oral hygiene
Semi-Supervised Word Sense Disambiguation Using Word Embeddings in General and Specific Domains