activity
20192024
most citedAutomatic Disfluency Detection from Untranscribed Speech

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20241 cited

From Text to Emotion: Unveiling the Emotion Annotation Capabilities of LLMs

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. In this paper, we explore the potential of La…

cs.CL2024

Why Antiwork: A RoBERTa-Based System for Work-Related Stress Identification and Leading Factor Analysis

Tao Lu, Muzhe Wu, Xinyi Lu +4

Harsh working environments and work-related stress have been known to contribute to mental health problems such as anxiety, depression, and suicidal ideation. As such, it is paramo…

cs.CL2024

Beyond Binary: Multiclass Paraphasia Detection with Generative Pretrained Transformers and End-to-End Models

Matthew Perez, Aneesha Sampath, Minxue Niu +1

Aphasia is a language disorder that can lead to speech errors known as paraphasias, which involve the misuse, substitution, or invention of words. Automatic paraphasia detection ca…

eess.AS20231 cited

Automatic Disfluency Detection from Untranscribed Speech

Amrit Romana, Kazuhito Koishida, Emily Mower Provost

Speech disfluencies, such as filled pauses or repetitions, are disruptions in the typical flow of speech. Stuttering is a speech disorder characterized by a high rate of disfluenci…

cs.LG2019

Trainable Time Warping: Aligning Time-Series in the Continuous-Time Domain

Soheil Khorram, Melvin G McInnis, Emily Mower Provost

DTW calculates the similarity or alignment between two signals, subject to temporal warping. However, its computational complexity grows exponentially with the number of time-serie…