5 citations · 6 across the 5 of their papers we have counts for
5 papers
The Illusion of AI Expertise Under Uncertainty: A Probabilistic Paradigm to Interpret Results Under Ground Truth Variation
Aparna Elangovan, Lei Xu, Mahsa Elyasi +8
Benchmarking the capabilities of AI systems, including Large Language Models (LLMs) and Vision Models, typically ignores the impact of uncertainty in the underlying ground truth an…
Beyond correlation: The Impact of Human Uncertainty in Measuring the Effectiveness of Automatic Evaluation and LLM-as-a-Judge
Aparna Elangovan, Lei Xu, Jongwoo Ko +4
The effectiveness of automatic evaluation of generative models is typically measured by comparing the labels generated via automation with labels by humans using correlation metric…
Grapheme-to-Phoneme Transformer Model for Transfer Learning Dialects
Eric Engelhart, Mahsa Elyasi, Gaurav Bharaj
Grapheme-to-Phoneme (G2P) models convert words to their phonetic pronunciations. Classic G2P methods include rule-based systems and pronunciation dictionaries, while modern G2P sys…
Flavored Tacotron: Conditional Learning for Prosodic-linguistic Features
Mahsa Elyasi, Gaurav Bharaj
Neural sequence-to-sequence text-to-speech synthesis (TTS), such as Tacotron-2, transforms text into high-quality speech. However, generating speech with natural prosody still rema…
Generalized Spoofing Detection Inspired from Audio Generation Artifacts
Yang Gao, Tyler Vuong, Mahsa Elyasi +2
State-of-the-art methods for audio generation suffer from fingerprint artifacts and repeated inconsistencies across temporal and spectral domains. Such artifacts could be well capt…