43 citations · 236 across the 34 of their papers we have counts for
15 papers · 1 filter
A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness
Tiantian Feng, Rajat Hebbar, Nicholas Mehlman +3
Speech-centric machine learning systems have revolutionized many leading domains ranging from transportation and healthcare to education and defense, profoundly changing how people…
A Context-Aware Computational Approach for Measuring Vocal Entrainment in Dyadic Conversations
Rimita Lahiri, Md Nasir, Catherine Lord +2
Vocal entrainment is a social adaptation mechanism in human interaction, knowledge of which can offer useful insights to an individual's cognitive-behavioral characteristics. We pr…
Can Knowledge of End-to-End Text-to-Speech Models Improve Neural MIDI-to-Audio Synthesis Systems?
Xuan Shi, Erica Cooper, Xin Wang +2
With the similarity between music and speech synthesis from symbolic input and the rapid development of text-to-speech (TTS) techniques, it is worthwhile to explore ways to improve…
Using Emotion Embeddings to Transfer Knowledge Between Emotions, Languages, and Annotation Formats
Georgios Chochlakis, Gireesh Mahajan, Sabyasachee Baruah +3
The need for emotional inference from text continues to diversify as more and more disciplines integrate emotions into their theories and applications. These needs include inferrin…
On the Role of Visual Context in Enriching Music Representations
Kleanthis Avramidis, Shanti Stewart, Shrikanth Narayanan
Human perception and experience of music is highly context-dependent. Contextual variability contributes to differences in how we interpret and interact with music, challenging the…
Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios
Zhuohao Chen, Nikolaos Flemotomos, Zac E. Imel +2
In psychotherapy interactions, the quality of a session is assessed by codifying the communicative behaviors of participants during the conversation through manual observation and…
MovieCLIP: Visual Scene Recognition in Movies
Digbalay Bose, Rajat Hebbar, Krishna Somandepalli +5
Longform media such as movies have complex narrative structures, with events spanning a rich variety of ambient visual scenes. Domain specific challenges associated with visual sce…
Leveraging Label Correlations in a Multi-label Setting: A Case Study in Emotion
Georgios Chochlakis, Gireesh Mahajan, Sabyasachee Baruah +3
Detecting emotions expressed in text has become critical to a range of fields. In this work, we investigate ways to exploit label correlations in multi-label emotion recognition mo…
FedAudio: A Federated Learning Benchmark for Audio Tasks
Tuo Zhang, Tiantian Feng, Samiul Alam +4
Federated learning (FL) has gained substantial attention in recent years due to the data privacy concerns related to the pervasiveness of consumer devices that continuously collect…
The 2022 Far-field Speaker Verification Challenge: Exploring domain mismatch and semi-supervised learning under the far-field scenario
Xiaoyi Qin, Ming Li, Hui Bu +2
FFSVC2022 is the second challenge of far-field speaker verification. FFSVC2022 provides the fully-supervised far-field speaker verification to further explore the far-field scenari…
VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media
Georgios Chochlakis, Tejas Srinivasan, Jesse Thomason +1
We propose the Vision-and-Augmented-Language Transformer (VAuLT). VAuLT is an extension of the popular Vision-and-Language Transformer (ViLT), and improves performance on vision-an…
User-Level Differential Privacy against Attribute Inference Attack of Speech Emotion Recognition in Federated Learning
Tiantian Feng, Raghuveer Peri, Shrikanth Narayanan
Many existing privacy-enhanced speech emotion recognition (SER) frameworks focus on perturbing the original speech data through adversarial training within a centralized machine le…
Mel Frequency Spectral Domain Defenses against Adversarial Attacks on Speech Recognition Systems
Nicholas Mehlman, Anirudh Sreeram, Raghuveer Peri +1
A variety of recent works have looked into defenses for deep neural networks against adversarial attacks particularly within the image processing domain. Speech processing applicat…
To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition
Raghuveer Peri, Krishna Somandepalli, Shrikanth Narayanan
Speaker recognition is increasingly used in several everyday applications including smart speakers, customer care centers and other speech-driven analytics. It is crucial to accura…
Semi-FedSER: Semi-supervised Learning for Speech Emotion Recognition On Federated Learning using Multiview Pseudo-Labeling
Tiantian Feng, Shrikanth Narayanan
Speech Emotion Recognition (SER) application is frequently associated with privacy concerns as it often acquires and transmits speech data at the client-side to remote cloud platfo…