no code implementations • 10 Dec 2024 • Minxue Niu, Yara El-Tawil, Amrit Romana, Emily Mower Provost
In this work, we analyze the complexities of emotion annotation in the context of LLMs, focusing on GPT-4 as a leading model.
1 code implementation • 30 Aug 2024 • Minxue Niu, Mimansa Jaiswal, Emily Mower Provost
Training emotion recognition models has relied heavily on human annotated data, which present diversity, quality, and cost challenges.
no code implementations • 24 Aug 2024 • Tao Lu, Muzhe Wu, Xinyi Lu, Siyuan Xu, Shuyu Zhan, Anuj Tambwekar, Emily Mower Provost
r/antiwork is a subreddit for the antiwork movement, which is the desire to stop working altogether.
1 code implementation • 21 Aug 2024 • James Tavernor, Yara El-Tawil, Emily Mower Provost
Previous work has attempted to learn distributions to capture emotion variability, but these methods also lose information about the individual annotators.
no code implementations • 16 Jul 2024 • Matthew Perez, Aneesha Sampath, Minxue Niu, Emily Mower Provost
Aphasia is a language disorder that can lead to speech errors known as paraphasias, which involve the misuse, substitution, or invention of words.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
2 code implementations • 16 Dec 2023 • Matthew Perez, Duc Le, Amrit Romana, Elise Jones, Keli Licata, Emily Mower Provost
In this paper, we propose a novel, sequence-to-sequence (seq2seq) model that is trained end-to-end (E2E) to perform both ASR and paraphasia detection tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
2 code implementations • 1 Nov 2023 • Amrit Romana, Kazuhito Koishida, Emily Mower Provost
We find that disfluency detection performance is largely limited by the quality of transcripts and alignments.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
1 code implementation • 28 Sep 2021 • Matthew Perez, Amrit Romana, Angela Roberts, Noelle Carlozzi, Jennifer Ann Miner, Praveen Dayalu, Emily Mower Provost
Lastly, we analyze the F-value scores of VTC features to visualize which channels are most related to motor score.
1 code implementation • 9 Sep 2021 • Lance Ying, Amrit Romana, Emily Mower Provost
In recent years, deep-learning-based speech emotion recognition models have outperformed classical machine learning models.
no code implementations • NAACL 2021 • Zakaria Aldeneh, Matthew Perez, Emily Mower Provost
Paralinguistics, the non-lexical components of speech, play a crucial role in human-human interaction.
no code implementations • 18 Apr 2021 • Mimansa Jaiswal, Emily Mower Provost
In this paper, we propose an automatic and quantifiable metric that allows us to evaluate humans' perception of a model's ability to preserve privacy with respect to sensitive variables.
no code implementations • 18 Apr 2021 • Mimansa Jaiswal, Emily Mower Provost
We end the paper with a set of recommendations for noise augmentations in speech emotion recognition datasets.
no code implementations • 21 Oct 2020 • Alex Wilf, Emily Mower Provost
Robustness to environmental noise is important to creating automatic speech emotion recognition systems that are deployable in the real world.
no code implementations • EMNLP (NLP-COVID19) 2020 • Laura Biester, Katie Matton, Janarthanan Rajendran, Emily Mower Provost, Rada Mihalcea
The COVID-19 pandemic, like many of the disease outbreaks that have preceded it, is likely to have a profound effect on mental health.
no code implementations • 7 Aug 2020 • Matthew Perez, Wenyu Jin, Duc Le, Noelle Carlozzi, Praveen Dayalu, Angela Roberts, Emily Mower Provost
Speech is a critical biomarker for Huntington Disease (HD), with changes in speech increasing in severity as the disease progresses.
no code implementations • LREC 2020 • Mimansa Jaiswal, Cristian-Paul Bara, Yuanhang Luo, Mihai Burzo, Rada Mihalcea, Emily Mower Provost
Endowing automated agents with the ability to provide support, entertainment and interaction with human beings requires sensing of the users{'} affective state.
no code implementations • 29 Oct 2019 • Mimansa Jaiswal, Emily Mower Provost
In this work, we show how multimodal representations trained for a primary task, here emotion recognition, can unintentionally leak demographic information, which could override a selected opt-out option by the user.
no code implementations • 29 Sep 2019 • Zakaria Aldeneh, Mimansa Jaiswal, Michael Picheny, Melvin McInnis, Emily Mower Provost
Bipolar disorder, a severe chronic mental illness characterized by pathological mood swings from depression to mania, requires ongoing symptom severity tracking to both guide and measure treatments that are critical for maintaining long-term health.
no code implementations • 25 Sep 2019 • John Gideon, Katie Matton, Steve Anderau, Melvin G McInnis, Emily Mower Provost
Predicting when to intervene is challenging because there is not a single measure that is relevant for every person: different individuals may have different levels of symptom severity considered typical.
no code implementations • 1 Sep 2019 • Vidhyasaharan Sethu, Emily Mower Provost, Julien Epps, Carlos Busso, NIcholas Cummins, Shrikanth Narayanan
A key reason for this is the lack of a common mathematical framework to describe all the relevant elements of emotion representations.
no code implementations • 23 Aug 2019 • Mimansa Jaiswal, Zakaria Aldeneh, Emily Mower Provost
Our results show that stress is indeed encoded in trained emotion classifiers and that this encoding varies across levels of emotions and across the lexical and acoustic modalities.
no code implementations • 5 Jul 2019 • Soheil Khorram, Melvin G McInnis, Emily Mower Provost
To deal with this challenge, we introduce a new convolutional neural network (multi-delay sinc network) that is able to simultaneously align and predict labels in an end-to-end manner.
no code implementations • 28 Mar 2019 • John Gideon, Melvin G McInnis, Emily Mower Provost
We also show how, in most cases, ADDoG and MADDoG can be used to improve upon baseline state-of-the-art methods when target dataset labels are added and in-the-wild data are considered.
no code implementations • 27 Mar 2019 • Mimansa Jaiswal, Zakaria Aldeneh, Cristian-Paul Bara, Yuanhang Luo, Mihai Burzo, Rada Mihalcea, Emily Mower Provost
As a result, annotations are colored by the manner in which they were collected.
1 code implementation • 21 Mar 2019 • Soheil Khorram, Melvin G McInnis, Emily Mower Provost
We introduce trainable time warping (TTW), whose complexity is linear in both the number and the length of time-series.
no code implementations • 9 May 2018 • Zakaria Aldeneh, Dimitrios Dimitriadis, Emily Mower Provost
This work focuses on the use of acoustic cues for modeling turn-taking in dyadic spoken dialogues.
no code implementations • 23 Aug 2017 • Soheil Khorram, Zakaria Aldeneh, Dimitrios Dimitriadis, Melvin McInnis, Emily Mower Provost
The goal of continuous emotion recognition is to assign an emotion value to every frame in a sequence of acoustic features.
1 code implementation • 10 Jun 2017 • John Gideon, Soheil Khorram, Zakaria Aldeneh, Dimitrios Dimitriadis, Emily Mower Provost
Many paralinguistic tasks are closely related and thus representations learned in one domain can be leveraged for another.
no code implementations • IEEE Transactions on Affective Computing 2016 • Carlos Busso, Srinivas Parthasarathy, Alec Burmania, Mohammed AbdelWahab, Najmeh Sadoughi, Emily Mower Provost
The paper also provides the performance for speech and facial emotion classifiers.