Nicholas Cummins — accepted AI-conference papers

2024

Longitudinal Modeling of Depression Shifts Using Speech and Language

Paula Andrea Pérez-Toro, Judith Dineley, Agnieszka Kaczkowska, Pauline Conde, Yuezhou Zhang, Faith Matcham +12

ICASSP 2024accepted

Speech analysis can provide a potential non-invasive and objective means of assessing and monitoring an individual’s mental health. Most studies to date have focused on cross-sectional analysis and have not explored the benefits of speech analysis as a longitudinal monitoring tool that can assist in…

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2021

Hierarchical Attention-Based Temporal Convolutional Networks for Eeg-Based Emotion Recognition

Chao Li, Boyang Chen, Ziping Zhao, Nicholas Cummins, Björn W. Schuller

ICASSP 2021accepted

EEG-based emotion recognition is an effective way to infer the inner emotional state of human beings. Recently, deep learning methods, particularly long short-term memory recurrent neural networks (LSTM-RNNs), have made encouraging progress for in the field of emotion recognition. However, the LSTM-…

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2020

Hierarchical Attention Transfer Networks for Depression Assessment from Speech

Ziping Zhao, Zhongtian Bao, Zixing Zhang, Nicholas Cummins, Haishuai Wang, Björn W. Schuller

ICASSP 2020accepted

A growing area of mental health research is the search for speech-based objective markers for conditions such as depression. However, when combined with machine learning, this search can be challenging due to a limited amount of annotated training data. In this paper, we propose a novel crosstask ap…

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2019

Context Modelling Using Hierarchical Attention Networks for Sentiment and Self-assessed Emotion Detection in Spoken Narratives

Lukas Stappen, Nicholas Cummins, Eva-Maria Meßner, Harald Baumeister, Judith Dineley, Björn W. Schuller

ICASSP 2019accepted

Automatic detection of sentiment and affect in personal narratives through word usage has the potential to assist in the automated detection of change in psychotherapy. Such a tool could, for instance, provide an efficient, objective measure of the time a person has been in a positive or negative st…

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2018

Multimodal Bag-of-Words for Cross Domains Sentiment Analysis

Nicholas Cummins, Shahin Amiriparian, Sandra Ottl, Maurice Gerczuk, Maximilian Schmitt, Björn W. Schuller

ICASSP 2018accepted

The advantages of using cross domain data when performing text-based sentiment analysis have been established; however, similar findings have yet to be observed when performing multimodal sentiment analysis. A potential reason for this is that systems based on feature extracted from speech and facia…

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2018

What is my Dog Trying to Tell Me? the Automatic Recognition of the Context and Perceived Emotion of Dog Barks

Simone Hantke, Nicholas Cummins, Björn W. Schuller

ICASSP 2018accepted

A wide range of research disciplines are deeply interested in the measurement of animal emotions, including evolutionary zoology, affective neuroscience and comparative psychology. However, only a few studies have investigated the effect of phenomena such as emotion on the acoustic parameters of (no…

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2015

Weighted pairwise Gaussian likelihood regression for depression score prediction

Nicholas Cummins, Julien Epps, Vidhyasaharan Sethu, Jarek Krajewski

ICASSP 2015accepted

This paper presents a technique in which feature vectors are mapped onto ordinal ranges of clinical depression scores using weighted pairwise Gaussians. The position of a test vector with respect to these partitions is used to perform depression score prediction. Results found on a set of spectral a…

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