patents

2021

1. Generating informative and accurate descriptions of natural hazards and phenomena using large transformer-based models

   Vasiliki Tassopoulou, Noah Kasmanoff, Vishvesh Soni, Fech Scen Khoo, Kevin Ward, and 5 more authors

   In AGU Fall Meeting Abstracts Dec 2021

2020

1. Nontrivial Lexical Convergence in a Geography-Themed Game

   Amanda Bergqvist, Ramesh Manuvinakurike, Deepthi Karkada, and Maike Paetzel

   In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue Jul 2020

   Abs

   The present study aims to examine the prevalent notion that people entrain to the vocabulary of a dialogue system. Although previous research shows that people will replace their choice of words with simple substitutes, studies using more challenging substitutions are sparse. In this paper, we investigate whether people adapt their speech to the vocabulary of a dialogue system when the system’s suggested words are not direct synonyms. 32 participants played a geography-themed game with a remote-controlled agent and were primed by referencing strategies (rather than individual terms) introduced in follow-up questions. Our results suggest that context-appropriate substitutes support convergence and that the convergence has a lasting effect within a dialogue session if the system’s wording is more consistent with the norms of the domain than the original wording of the speaker.

2. RDG-Map: A Multimodal Corpus of Pedagogical Human-Agent Spoken Interactions.

   Maike Paetzel, Deepthi Karkada, and Ramesh Manuvinakurike

   In Proceedings of the Twelfth Language Resources and Evaluation Conference May 2020

   Abs

   This paper presents a multimodal corpus of 209 spoken game dialogues between a human and a remote-controlled artificial agent. The interactions involve people collaborating with the agent to identify countries on the world map as quickly as possible, which allows studying rapid and spontaneous dialogue with complex anaphoras, disfluent utterances and incorrect descriptions. The corpus consists of two parts: 8 hours of game interactions have been collected with a virtual unembodied agent online and 26.8 hours have been recorded with a physically embodied robot in a research lab. In addition to spoken audio recordings available for both parts, camera recordings and skeleton-, facial expression- and eye-gaze tracking data have been collected for the lab-based part of the corpus. In this paper, we introduce the pedagogical reference resolution game (RDG-Map) and the characteristics of the corpus collected. We also present an annotation scheme we developed in order to study the dialogue strategies utilized by the players. Based on a subset of 330 minutes of interactions annotated so far, we discuss initial insights into these strategies as well as the potential of the corpus for future research.

2019

1. Efficient 8-Bit Quantization of Transformer Neural Machine Language Translation Model

   Aishwarya Bhandare, Vamsi Sripathi, Deepthi Karkada, Vivek Menon, Sun Choi, and 2 more authors

   CoRR May 2019
2. Best practices for scaling deep learning training and inference with tensorflow on intel xeon processor-based hpc infrastructures

   Aishwarya Bhandare, Deepthi Karkada, Kushal Datta, Anupama Kurpad, Vamsi Sripathi, and 2 more authors

   Connectivity Group & AI Products Group, Data Center Group Customer Solutions Technical Enabling, Intel Corporation, Tech. Rep May 2019

2018

1. Training Speech Recognition Models on HPC Infrastructure

   Deepthi Karkada, and Vikram A. Saletore

   In 2018 IEEE/ACM Machine Learning in HPC Environments (MLHPC) May 2018
2. Towards Understanding End-of-trip Instructions in a Taxi Ride Scenario

   Deepthi Karkada, Ramesh R. Manuvinakurike, and Kallirroi Georgila

   CoRR May 2018