Search Results for author:
Found 18 papers, 4 papers with code
Dissociating Semantic and Phonemic Search Strategies in the Phonemic Verbal Fluency Task in early Dementia
Specifically, we show that subjects with MCI rely less on semantic- and more on phonemic processes to guide their word production as compared to healthy controls (HC).
Multilingual Learning for Mild Cognitive Impairment Screening from a Clinical Speech Task
The Semantic Verbal Fluency Task (SVF) is an efficient and minimally invasive speech-based screening tool for Mild Cognitive Impairment (MCI).
Generating Synthetic Clinical Speech Data through Simulated ASR Deletion Error
Training classification models on clinical speech is a time-saving and effective solution for many healthcare challenges, such as screening for Alzheimer’s Disease over the phone.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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M3TCM: Multi-modal Multi-task Context Model for Utterance Classification in Motivational Interviews
Accurate utterance classification in motivational interviews is crucial to automatically understand the quality and dynamics of client-therapist interaction, and it can serve as a key input for systems mediating such interactions.
Classification of Volatile Organic Compounds by Differential Mobility Spectrometry Based on Continuity of Alpha Curves
Measurements collected with electronic noses can be used for classification and analysis of VOCs.
NeMig -- A Bilingual News Collection and Knowledge Graph about Migration
News recommendation plays a critical role in shaping the public's worldviews through the way in which it filters and disseminates information about different topics.
MultiMediate'23: Engagement Estimation and Bodily Behaviour Recognition in Social Interactions
This paper describes the MultiMediate'23 challenge and presents novel sets of annotations for both tasks.
Backchannel Detection and Agreement Estimation from Video with Transformer Networks
Listeners use short interjections, so-called backchannels, to signify attention or express agreement.
Flexible K Nearest Neighbors Classifier: Derivation and Application for Ion-mobility Spectrometry-based Indoor Localization
It determines the class membership of unlabelled sample based on the class memberships of the K labelled samples, the so-called nearest neighbors, that are closest to the unlabelled sample.
Multimodal Vision Transformers with Forced Attention for Behavior Analysis
Human behavior understanding requires looking at minute details in the large context of a scene containing multiple input modalities.
Bodily Behaviors in Social Interaction: Novel Annotations and State-of-the-Art Evaluation
Body language is an eye-catching social signal and its automatic analysis can significantly advance artificial intelligence systems to understand and actively participate in social interactions.
Gaze-enhanced Crossmodal Embeddings for Emotion Recognition
Emotional expressions are inherently multimodal -- integrating facial behavior, speech, and gaze -- but their automatic recognition is often limited to a single modality, e. g. speech during a phone call.
Towards Analyzing the Bias of News Recommender Systems Using Sentiment and Stance Detection
News recommender systems are used by online news providers to alleviate information overload and to provide personalized content to users.
Multimodal Integration of Human-Like Attention in Visual Question Answering
We present the Multimodal Human-like Attention Network (MULAN) - the first method for multimodal integration of human-like attention on image and text during training of VQA models.
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO
To achieve peak predictive performance, hyperparameter optimization (HPO) is a crucial component of machine learning and its applications.
Neural Photofit: Gaze-based Mental Image Reconstruction
The encoder extracts image features and predicts a neural activation map for each face looked at by a human observer.
Neural Model-based Optimization with Right-Censored Observations
When fitting a regression model to predict the distribution of the outcomes, we cannot simply drop these right-censored observations, but need to properly model them.
BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters
Hyperparameter optimization and neural architecture search can become prohibitively expensive for regular black-box Bayesian optimization because the training and evaluation of a single model can easily take several hours.
