65 citations · 79 across the 18 of their papers we have counts for
20 papers
Evaluation-as-Search: Adaptive Discovery of Grounding Failures in Meeting Assistants
Sami Khairy, Yasaman Hosseinkashi, Vishak Gopal +1
LLM-powered meeting assistants are deployed at scale, yet systematic evaluation of their grounding fidelity remains limited to static benchmarks that miss failure modes tied to spe…
Human-in-the-Loop Bandwidth Estimation for Quality of Experience Optimization in Real-Time Video Communication
Sami Khairy, Gabriel Mittag, Vishak Gopal +1
The quality of experience (QoE) delivered by video conferencing systems is significantly influenced by accurately estimating the time-varying available bandwidth between the sender…
Streetwise Agents: Empowering Offline RL Policies to Outsmart Exogenous Stochastic Disturbances in RTC
Aditya Soni, Mayukh Das, Anjaly Parayil +8
The difficulty of exploring and training online on real production systems limits the scope of real-time online data/feedback-driven decision making. The most feasible approach is…
A multidimensional measurement of photorealistic avatar quality of experience
Ross Cutler, Babak Naderi, Vishak Gopal +1
Photorealistic avatars are human avatars that look, move, and talk like real people. The performance of photorealistic avatars has significantly improved recently based on objectiv…
Offline Meta-learning for Real-time Bandwidth Estimation
Aashish Gottipati, Sami Khairy, Yasaman Hosseinkashi +4
Real-time video applications require dynamic bitrate adjustments based on network capacity, necessitating accurate bandwidth estimation (BWE). We introduce Ivy, a novel BWE method…
ACM MMSys 2024 Bandwidth Estimation in Real Time Communications Challenge
Sami Khairy, Gabriel Mittag, Vishak Gopal +6
The quality of experience (QoE) delivered by video conferencing systems to end users depends in part on correctly estimating the capacity of the bottleneck link between the sender…
A Real-Time Active Speaker Detection System Integrating an Audio-Visual Signal with a Spatial Querying Mechanism
Ilya Gurvich, Ido Leichter, Dharmendar Reddy Palle +6
We introduce a distinctive real-time, causal, neural network-based active speaker detection system optimized for low-power edge computing. This system drives a virtual cinematograp…
Offline to Online Learning for Real-Time Bandwidth Estimation
Aashish Gottipati, Sami Khairy, Gabriel Mittag +2
Real-time video applications require accurate bandwidth estimation (BWE) to maintain user experience across varying network conditions. However, increasing network heterogeneity ch…
LSTM-based Video Quality Prediction Accounting for Temporal Distortions in Videoconferencing Calls
Gabriel Mittag, Babak Naderi, Vishak Gopal +1
Current state-of-the-art video quality models, such as VMAF, give excellent prediction results by comparing the degraded video with its reference video. However, they do not consid…
ICASSP 2023 Deep Noise Suppression Challenge
Harishchandra Dubey, Ashkan Aazami, Vishak Gopal +9
Deep Speech Enhancement Challenge is the 5th edition of deep noise suppression (DNS) challenges organized at ICASSP 2023 Signal Processing Grand Challenges. DNS challenges were org…
ICASSP 2022 Deep Noise Suppression Challenge
Harishchandra Dubey, Vishak Gopal, Ross Cutler +8
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. This is the 4th DNS chal…
Performance optimizations on deep noise suppression models
Jerry Chee, Sebastian Braun, Vishak Gopal +1
We study the role of magnitude structured pruning as an architecture search to speed up the inference time of a deep noise suppression (DNS) model. While deep learning approaches h…
DNSMOS P.835: A Non-Intrusive Perceptual Objective Speech Quality Metric to Evaluate Noise Suppressors
Chandan K A Reddy, Vishak Gopal, Ross Cutler
Human subjective evaluation is the gold standard to evaluate speech quality optimized for human perception. Perceptual objective metrics serve as a proxy for subjective scores. We…
Interspeech 2021 Deep Noise Suppression Challenge
Chandan K A Reddy, Harishchandra Dubey, Kazuhito Koishida +7
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. We recently organized a…
Resonance: Replacing Software Constants with Context-Aware Models in Real-time Communication
Jayant Gupchup, Ashkan Aazami, Yaran Fan +23
Large software systems tune hundreds of 'constants' to optimize their runtime performance. These values are commonly derived through intuition, lab tests, or A/B tests. A 'one-size…
ICASSP 2021 Deep Noise Suppression Challenge
Chandan K A Reddy, Harishchandra Dubey, Vishak Gopal +5
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. We recently organized a…
DNSMOS: A Non-Intrusive Perceptual Objective Speech Quality metric to evaluate Noise Suppressors
Chandan K A Reddy, Vishak Gopal, Ross Cutler
Human subjective evaluation is the gold standard to evaluate speech quality optimized for human perception. Perceptual objective metrics serve as a proxy for subjective scores. The…
Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications
Jamie Pool, Ebrahim Beyrami, Vishak Gopal +7
Web-scale applications can ship code on a daily to weekly cadence. These applications rely on online metrics to monitor the health of new releases. Regressions in metric values nee…
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results
Chandan K. A. Reddy, Vishak Gopal, Ross Cutler +10
The INTERSPEECH 2020 Deep Noise Suppression (DNS) Challenge is intended to promote collaborative research in real-time single-channel Speech Enhancement aimed to maximize the subje…
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework
Chandan K. A. Reddy, Ebrahim Beyrami, Harishchandra Dubey +10
The INTERSPEECH 2020 Deep Noise Suppression Challenge is intended to promote collaborative research in real-time single-channel Speech Enhancement aimed to maximize the subjective…