Anthony Ferritto — accepted AI-conference papers

2025

Improving Lip-synchrony in Direct Audio-Visual Speech-to-Speech Translation

Lucas Goncalves, Prashant Mathur, Xing Niu, Chandrashekhar Lavania, Brady Houston, Srikanth Vishnubhotla +2

ICASSP 2025accepted

Audio-Visual Speech-to-Speech Translation (AVS2S) typically prioritizes improving translation quality and naturalness. However, an equally critical aspect in audio-visual content is lip-synchrony—ensuring that the movements of the lips match the spoken content—essential for maintaining realism in du…

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2023

GAAMA 2.0: An Integrated System That Answers Boolean and Extractive Questions

Scott McCarley, Mihaela Bornea, Sara Rosenthal, Anthony Ferritto, Md Arafat Sultan, Avirup Sil +1

AAAI 2023technical

Recent machine reading comprehension datasets include extractive and boolean questions but current approaches do not offer integrated support for answering both question types. We present a front-end demo to a multilingual machine reading comprehension system that handles boolean and extractive ques…

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2021

VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension

Haoyang Wen, Anthony Ferritto, Heng Ji, Radu Florian, Avi Sil

ACL 2021short

Existing models on Machine Reading Comprehension (MRC) require complex model architecture for effectively modeling long texts with paragraph representation and classification, thereby making inference computationally inefficient for production use. In this work, we propose VAULT: a light-weight and…

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2020

A Multilingual Reading Comprehension System for more than 100 Languages

Anthony Ferritto, Sara Rosenthal, Mihaela Bornea, Kazi Hasan, Rishav Chakravarti, Salim Roukos +2

COLING 2020system demonstrations

This paper presents M-GAAMA, a Multilingual Question Answering architecture and demo system. This is the first multilingual machine reading comprehension (MRC) demo which is able to answer questions in over 100 languages. M-GAAMA answers questions from a given passage in the same or different langua…

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2020

Towards building a Robust Industry-scale Question Answering System

Rishav Chakravarti, Anthony Ferritto, Bhavani Iyer, Lin Pan, Radu Florian, Salim Roukos +1

COLING 2020industry

Industry-scale NLP systems necessitate two features. 1. Robustness: “zero-shot transfer learning” (ZSTL) performance has to be commendable and 2. Efficiency: systems have to train efficiently and respond instantaneously. In this paper, we introduce the development of a production model called GAAMA…

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