Search Results for author: Shrikanth Narayanan

Found 74 papers, 12 papers with code

Joint Estimation and Analysis of Risk Behavior Ratings in Movie Scripts

no code implementations EMNLP 2020 Victor Martinez, Krishna Somandepalli, Yalda Tehranian-Uhls, Shrikanth Narayanan

Exposure to violent, sexual, or substance-abuse content in media increases the willingness of children and adolescents to imitate similar behaviors.

Local dynamic mode of Cognitive Behavioral Therapy

no code implementations28 Apr 2022 Victor Ardulov, Torrey A. Creed, David C. Atkins, Shrikanth Narayanan

In order to increase mental health equity among the most vulnerable and marginalized communities, it is important to increase access to high-quality therapists.

Multimodal Clustering with Role Induced Constraints for Speaker Diarization

no code implementations1 Apr 2022 Nikolaos Flemotomos, Shrikanth Narayanan

Speaker clustering is an essential step in conventional speaker diarization systems and is typically addressed as an audio-only speech processing task.

Speaker Diarization

Using Active Speaker Faces for Diarization in TV shows

no code implementations30 Mar 2022 Rahul Sharma, Shrikanth Narayanan

Speaker diarization is one of the critical components of computational media intelligence as it enables a character-level analysis of story portrayals and media content understanding.

Face Clustering Face Detection +1

Mel Frequency Spectral Domain Defenses against Adversarial Attacks on Speech Recognition Systems

no code implementations29 Mar 2022 Nicholas Mehlman, Anirudh Sreeram, Raghuveer Peri, Shrikanth Narayanan

A variety of recent works have looked into defenses for deep neural networks against adversarial attacks particularly within the image processing domain.

Automatic Speech Recognition

Audio visual character profiles for detecting background characters in entertainment media

no code implementations21 Mar 2022 Rahul Sharma, Shrikanth Narayanan

We curate a background character dataset which provides annotations for background character for a set of TV shows, and use it to evaluate the performance of the background character detection framework.

Active Speaker Localization Face Verification

To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition

1 code implementation17 Mar 2022 Raghuveer Peri, Krishna Somandepalli, Shrikanth Narayanan

In this paper, we systematically evaluate the biases present in speaker recognition systems with respect to gender across a range of system operating points.

Face Recognition Fairness +2

Semi-FedSER: Semi-supervised Learning for Speech Emotion Recognition On Federated Learning using Multiview Pseudo-Labeling

1 code implementation15 Mar 2022 Tiantian Feng, Shrikanth Narayanan

In this work, we propose a semi-supervised federated learning framework, Semi-FedSER, that utilizes both labeled and unlabeled data samples to address the challenge of limited labeled data samples in FL.

Federated Learning Speech Emotion Recognition

Understanding of Emotion Perception from Art

no code implementations13 Oct 2021 Digbalay Bose, Krishna Somandepalli, Souvik Kundu, Rimita Lahiri, Jonathan Gratch, Shrikanth Narayanan

Computational modeling of the emotions evoked by art in humans is a challenging problem because of the subjective and nuanced nature of art and affective signals.

Cross Domain Emotion Recognition using Few Shot Knowledge Transfer

no code implementations11 Oct 2021 Justin Olah, Sabyasachee Baruah, Digbalay Bose, Shrikanth Narayanan

Emotion recognition from text is a challenging task due to diverse emotion taxonomies, lack of reliable labeled data in different domains, and highly subjective annotation standards.

Emotion Recognition Transfer Learning

Representation of professions in entertainment media: Insights into frequency and sentiment trends through computational text analysis

1 code implementation8 Oct 2021 Sabyasachee Baruah, Krishna Somandepalli, Shrikanth Narayanan

We analyze the frequency and sentiment trends of different occupations, study the effect of media attributes like genre, country of production, and title type on these trends, and investigate if the incidence of professions in media subtitles correlate with their real-world employment statistics.

Natural Language Processing

Phone Duration Modeling for Speaker Age Estimation in Children

no code implementations3 Sep 2021 Prashanth Gurunath Shivakumar, Somer Bishop, Catherine Lord, Shrikanth Narayanan

In this paper, we propose features specific to children and focus on speaker's phone duration as an important biomarker of children's age.

Age Estimation

An Automated Quality Evaluation Framework of Psychotherapy Conversations with Local Quality Estimates

no code implementations15 Jun 2021 Zhuohao Chen, Nikolaos Flemotomos, Karan Singla, Torrey A. Creed, David C. Atkins, Shrikanth Narayanan

In particular, we model the global quality as a linear function of the local quality scores, which allows us to update the segment-level quality estimates based on the session-level quality prediction.

Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition

no code implementations5 Apr 2021 Haoqi Li, Yelin Kim, Cheng-Hao Kuo, Shrikanth Narayanan

Key challenges in developing generalized automatic emotion recognition systems include scarcity of labeled data and lack of gold-standard references.

Domain Adaptation Emotion Recognition +1

Unsupervised Speech Representation Learning for Behavior Modeling using Triplet Enhanced Contextualized Networks

no code implementations1 Apr 2021 Haoqi Li, Brian Baucom, Shrikanth Narayanan, Panayiotis Georgiou

In this paper, we exploit the stationary properties of human behavior within an interaction and present a representation learning method to capture behavioral information from speech in an unsupervised way.

Representation Learning

Front-end Diarization for Percussion Separation in Taniavartanam of Carnatic Music Concerts

no code implementations4 Mar 2021 Nauman Dawalatabad, Jilt Sebastian, Jom Kuriakose, C. Chandra Sekhar, Shrikanth Narayanan, Hema A. Murthy

In this work, we address the problem of separating the percussive voices in the taniavartanam segments of Carnatic music.

Automated Quality Assessment of Cognitive Behavioral Therapy Sessions Through Highly Contextualized Language Representations

no code implementations23 Feb 2021 Nikolaos Flemotomos, Victor R. Martinez, Zhuohao Chen, Torrey A. Creed, David C. Atkins, Shrikanth Narayanan

In this work, we propose a BERT-based model for automatic behavioral scoring of a specific type of psychotherapy, called Cognitive Behavioral Therapy (CBT), where prior work is limited to frequency-based language features and/or short text excerpts which do not capture the unique elements involved in a spontaneous long conversational interaction.

Automated Evaluation Of Psychotherapy Skills Using Speech And Language Technologies

no code implementations22 Feb 2021 Nikolaos Flemotomos, Victor R. Martinez, Zhuohao Chen, Karan Singla, Victor Ardulov, Raghuveer Peri, Derek D. Caperton, James Gibson, Michael J. Tanana, Panayiotis Georgiou, Jake Van Epps, Sarah P. Lord, Tad Hirsch, Zac E. Imel, David C. Atkins, Shrikanth Narayanan

With the growing prevalence of psychological interventions, it is vital to have measures which rate the effectiveness of psychological care to assist in training, supervision, and quality assurance of services.

End-to-End Neural Systems for Automatic Children Speech Recognition: An Empirical Study

no code implementations19 Feb 2021 Prashanth Gurunath Shivakumar, Shrikanth Narayanan

A key desiderata for inclusive and accessible speech recognition technology is ensuring its robust performance to children's speech.

Speech Recognition

Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with Subwords

1 code implementation3 Feb 2021 Prashanth Gurunath Shivakumar, Panayiotis Georgiou, Shrikanth Narayanan

Confusion2vec, motivated from human speech production and perception, is a word vector representation which encodes ambiguities present in human spoken language in addition to semantics and syntactic information.

Automatic Speech Recognition Intent Detection +3

A Review of Speaker Diarization: Recent Advances with Deep Learning

no code implementations24 Jan 2021 Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis, Kyu J. Han, Shinji Watanabe, Shrikanth Narayanan

Speaker diarization is a task to label audio or video recordings with classes that correspond to speaker identity, or in short, a task to identify "who spoke when".

Speaker Diarization Speech Recognition

Robust Character Labeling in Movie Videos: Data Resources and Self-supervised Feature Adaptation

no code implementations25 Aug 2020 Krishna Somandepalli, Rajat Hebbar, Shrikanth Narayanan

Our work in this paper focuses on two key aspects of this problem: the lack of domain-specific training or benchmark datasets, and adapting face embeddings learned on web images to long-form content, specifically movies.

Domain Adaptation Face Clustering +1

Victim or Perpetrator? Analysis of Violent Characters Portrayals from Movie Scripts

no code implementations19 Aug 2020 Victor R. Martinez, Krishna Somandepalli, Karan Singla, Anil Ramanakrishna, Yalda T. Uhls, Shrikanth Narayanan

To date, we are the first to show that language used in movie scripts is a strong indicator of violent content, and that there are systematic portrayals of certain demographics as victims and perpetrators in a large dataset.

Adversarial Attack and Defense Strategies for Deep Speaker Recognition Systems

1 code implementation18 Aug 2020 Arindam Jati, Chin-Cheng Hsu, Monisankha Pal, Raghuveer Peri, Wael Abd-Almageed, Shrikanth Narayanan

Robust speaker recognition, including in the presence of malicious attacks, is becoming increasingly important and essential, especially due to the proliferation of several smart speakers and personal agents that interact with an individual's voice commands to perform diverse, and even sensitive tasks.

Adversarial Attack Adversarial Robustness +1

Designing Neural Speaker Embeddings with Meta Learning

1 code implementation31 Jul 2020 Manoj Kumar, Tae Jin-Park, Somer Bishop, Shrikanth Narayanan

Our experiments illustrate the applicability of meta-learning as a generalized learning paradigm for training deep neural speaker embeddings.

Audio and Speech Processing Sound

Evidence of Task-Independent Person-Specific Signatures in EEG using Subspace Techniques

no code implementations27 Jul 2020 Mari Ganesh Kumar, Shrikanth Narayanan, Mriganka Sur, Hema A. Murthy

These high dimensional statistics are then projected to a lower dimensional space where the biometric information is preserved.

EEG Speaker Recognition +1

Towards end-2-end learning for predicting behavior codes from spoken utterances in psychotherapy conversations

no code implementations ACL 2020 Karan Singla, Zhuohao Chen, David Atkins, Shrikanth Narayanan

Spoken language understanding tasks usually rely on pipelines involving complex processing blocks such as voice activity detection, speaker diarization and Automatic speech recognition (ASR).

Action Detection Activity Detection +3

Screenplay Quality Assessment: Can We Predict Who Gets Nominated?

no code implementations WS 2020 Ming-Chang Chiu, Tiantian Feng, Xiang Ren, Shrikanth Narayanan

Toward that goal, in this work, we present a method to evaluate the quality of a screenplay based on linguistic cues.

Generalized Multi-view Shared Subspace Learning using View Bootstrapping

no code implementations12 May 2020 Krishna Somandepalli, Shrikanth Narayanan

A key objective in multi-view learning is to model the information common to multiple parallel views of a class of objects/events to improve downstream learning tasks.

3D Object Classification Face Recognition +2

Joint Multi-Dimensional Model for Global and Time-Series Annotations

no code implementations6 May 2020 Anil Ramakrishna, Rahul Gupta, Shrikanth Narayanan

In this work we address this by proposing a generative model for multi-dimensional annotation fusion, which models the dimensions jointly leading to more accurate ground truth estimates.

Time Series

Speaker Diarization with Lexical Information

no code implementations13 Apr 2020 Tae Jin Park, Kyu J. Han, Jing Huang, Xiaodong He, Bo-Wen Zhou, Panayiotis Georgiou, Shrikanth Narayanan

This work presents a novel approach for speaker diarization to leverage lexical information provided by automatic speech recognition.

Automatic Speech Recognition Speaker Diarization

TILES-2018, a longitudinal physiologic and behavioral data set of hospital workers

no code implementations18 Mar 2020 Karel Mundnich, Brandon M. Booth, Michelle L'Hommedieu, Tiantian Feng, Benjamin Girault, Justin L'Hommedieu, Mackenzie Wildman, Sophia Skaaden, Amrutha Nadarajan, Jennifer L. Villatte, Tiago H. Falk, Kristina Lerman, Emilio Ferrara, Shrikanth Narayanan

We designed the study to investigate the use of off-the-shelf wearable and environmental sensors to understand individual-specific constructs such as job performance, interpersonal interaction, and well-being of hospital workers over time in their natural day-to-day job settings.

Privacy Preserving

A Label Proportions Estimation Technique for Adversarial Domain Adaptation in Text Classification

no code implementations16 Mar 2020 Zhuohao Chen, Singla Karan, David C. Atkins, Zac E. Imel, Shrikanth Narayanan

The DAN-LPE simultaneously trains a domain adversarial net and processes label proportions estimation by the confusion of the source domain and the predictions of the target domain.

Classification General Classification +2

Cross modal video representations for weakly supervised active speaker localization

no code implementations9 Mar 2020 Rahul Sharma, Krishna Somandepalli, Shrikanth Narayanan

Avoiding the need for manual annotations for active speakers in visual frames, acquiring of which is very expensive, we present a weakly supervised system for the task of localizing active speakers in movie content.

Action Detection Active Speaker Localization +2

Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap

2 code implementations5 Mar 2020 Tae Jin Park, Kyu J. Han, Manoj Kumar, Shrikanth Narayanan

In this study, we propose a new spectral clustering framework that can auto-tune the parameters of the clustering algorithm in the context of speaker diarization.

Speaker Diarization

An analysis of observation length requirements for machine understanding of human behaviors from spoken language

no code implementations21 Nov 2019 Sandeep Nallan Chakravarthula, Brian Baucom, Shrikanth Narayanan, Panayiotis Georgiou

In this paper, we investigate this link and present an analysis framework that determines appropriate window lengths for the task of behavior estimation.

Learning Behavioral Representations from Wearable Sensors

no code implementations16 Nov 2019 Nazgol Tavabi, Homa Hosseinmardi, Jennifer L. Villatte, Andrés Abeliuk, Shrikanth Narayanan, Emilio Ferrara, Kristina Lerman

Continuous collection of physiological data from wearable sensors enables temporal characterization of individual behaviors.

Characterizing dynamically varying acoustic scenes from egocentric audio recordings in workplace setting

no code implementations10 Nov 2019 Arindam Jati, Amrutha Nadarajan, Karel Mundnich, Shrikanth Narayanan

In this paper, we address the task of characterizing acoustic scenes in a workplace setting from audio recordings collected with wearable microphones.

Acoustic Scene Classification General Classification +1

Speaker-invariant Affective Representation Learning via Adversarial Training

no code implementations4 Nov 2019 Haoqi Li, Ming Tu, Jing Huang, Shrikanth Narayanan, Panayiotis Georgiou

In this paper, we propose a machine learning framework to obtain speech emotion representations by limiting the effect of speaker variability in the speech signals.

Emotion Classification Representation Learning +1

Robust speaker recognition using unsupervised adversarial invariance

1 code implementation3 Nov 2019 Raghuveer Peri, Monisankha Pal, Arindam Jati, Krishna Somandepalli, Shrikanth Narayanan

In this paper, we address the problem of speaker recognition in challenging acoustic conditions using a novel method to extract robust speaker-discriminative speech representations.

Speaker Diarization Speaker Recognition +1

Learning Domain Invariant Representations for Child-Adult Classification from Speech

no code implementations25 Oct 2019 Rimita Lahiri, Manoj Kumar, Somer Bishop, Shrikanth Narayanan

Diagnostic procedures for ASD (autism spectrum disorder) involve semi-naturalistic interactions between the child and a clinician.

General Classification

RNN based Incremental Online Spoken Language Understanding

no code implementations23 Oct 2019 Prashanth Gurunath Shivakumar, Naveen Kumar, Panayiotis Georgiou, Shrikanth Narayanan

We introduce and analyze different recurrent neural network architectures for incremental and online processing of the ASR transcripts and compare it to the existing offline systems.

Automatic Speech Recognition Intent Classification +3

Multimodal Embeddings from Language Models

1 code implementation10 Sep 2019 Shao-Yen Tseng, Panayiotis Georgiou, Shrikanth Narayanan

Word embeddings such as ELMo have recently been shown to model word semantics with greater efficacy through contextualized learning on large-scale language corpora, resulting in significant improvement in state of the art across many natural language tasks.

Emotion Recognition Language Modelling +1

The Ambiguous World of Emotion Representation

no code implementations1 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.

Face Recognition Speaker Verification +1

Behavior Gated Language Models

no code implementations31 Aug 2019 Prashanth Gurunath Shivakumar, Shao-Yen Tseng, Panayiotis Georgiou, Shrikanth Narayanan

In this work we derive motivation from psycholinguistics and propose the addition of behavioral information into the context of language modeling.

Language Modelling

Modeling Interpersonal Linguistic Coordination in Conversations using Word Mover's Distance

no code implementations12 Apr 2019 Md Nasir, Sandeep Nallan Chakravarthula, Brian Baucom, David C. Atkins, Panayiotis Georgiou, Shrikanth Narayanan

We find that our proposed measure is correlated with the therapist's empathy towards their patient in Motivational Interviewing and with affective behaviors in Couples Therapy.

Multimodal Representation Learning using Deep Multiset Canonical Correlation

1 code implementation3 Apr 2019 Krishna Somandepalli, Naveen Kumar, Ruchir Travadi, Shrikanth Narayanan

We propose Deep Multiset Canonical Correlation Analysis (dMCCA) as an extension to representation learning using CCA when the underlying signal is observed across multiple (more than two) modalities.

Representation Learning

On evaluating CNN representations for low resource medical image classification

no code implementations26 Mar 2019 Taruna Agrawal, Rahul Gupta, Shrikanth Narayanan

Convolutional Neural Networks (CNNs) have revolutionized performances in several machine learning tasks such as image classification, object tracking, and keyword spotting.

General Classification Image Classification +4

Multi-label Multi-task Deep Learning for Behavioral Coding

no code implementations29 Oct 2018 James Gibson, David C. Atkins, Torrey Creed, Zac Imel, Panayiotis Georgiou, Shrikanth Narayanan

We propose a methodology for estimating human behaviors in psychotherapy sessions using mutli-label and multi-task learning paradigms.

Multi-Task Learning

Tensor Embedding: A Supervised Framework for Human Behavioral Data Mining and Prediction

no code implementations31 Aug 2018 Homa Hosseinmardi, Amir Ghasemian, Shrikanth Narayanan, Kristina Lerman, Emilio Ferrara

Today's densely instrumented world offers tremendous opportunities for continuous acquisition and analysis of multimodal sensor data providing temporal characterization of an individual's behaviors.

Towards an Unsupervised Entrainment Distance in Conversational Speech using Deep Neural Networks

no code implementations23 Apr 2018 Md Nasir, Brian Baucom, Shrikanth Narayanan, Panayiotis Georgiou

Entrainment is a known adaptation mechanism that causes interaction participants to adapt or synchronize their acoustic characteristics.

Linguistic analysis of differences in portrayal of movie characters

no code implementations ACL 2017 Anil Ramakrishna, Victor R. Mart{\'\i}nez, Mal, Nikolaos rakis, Karan Singla, Shrikanth Narayanan

We examine differences in portrayal of characters in movies using psycholinguistic and graph theoretic measures computed directly from screenplays.

Inferring object rankings based on noisy pairwise comparisons from multiple annotators

no code implementations13 Dec 2016 Rahul Gupta, Shrikanth Narayanan

In this work, we propose Expectation-Maximization (EM) based algorithms that rely on the judgments from multiple annotators and the object attributes for inferring the latent ground truth.

The Twins Corpus of Museum Visitor Questions

no code implementations LREC 2012 Priti Aggarwal, Ron artstein, Jillian Gerten, Athanasios Katsamanis, Shrikanth Narayanan, Angela Nazarian, David Traum

In addition to speech recordings, the corpus contains the outputs of speech recognition performed at the time of utterance as well as the system interpretation of the utterances.

Dialogue Management Natural Language Understanding +2

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