activity
20192021
most citedA Comparison of Online Automatic Speech Recognition Systems and the Nonverbal Responses to Unintelligible Speech

17 citations · 27 across the 4 of their papers we have counts for

collaborators

5 papers

cs.HC2021

An empirical user-study of text-based nonverbal annotation systems for human-human conversations

Joshua Y. Kim, Kalina Yacef

the substantial increase in the number of online human-human conversations and the usefulness of multimodal transcripts, there is a rising need for automated multimodal transcripti…

cs.CL2021

MONAH: Multi-Modal Narratives for Humans to analyze conversations

Joshua Y. Kim, Greyson Y. Kim, Chunfeng Liu +3

In conversational analyses, humans manually weave multimodal information into the transcripts, which is significantly time-consuming. We introduce a system that automatically expan…

cs.HC2020★ 6 cited

Detecting depression in dyadic conversations with multimodal narratives and visualizations

Joshua Y. Kim, Greyson Y. Kim, Kalina Yacef

Conversations contain a wide spectrum of multimodal information that gives us hints about the emotions and moods of the speaker. In this paper, we developed a system that supports…

cs.HC2019★ 4 cited

A Review on Dyadic Conversation Visualizations - Purposes, Data, Lens of Analysis

Joshua Y. Kim, Rafael A. Calvo, Kalina Yacef +1

Many professional services are provided through text and voice systems, from voice calls over the internet to messaging and emails. There is a growing need for both individuals and…

cs.SD2019★ 17 cited

A Comparison of Online Automatic Speech Recognition Systems and the Nonverbal Responses to Unintelligible Speech

Joshua Y. Kim, Chunfeng Liu, Rafael A. Calvo +4

Automatic Speech Recognition (ASR) systems have proliferated over the recent years to the point that free platforms such as YouTube now provide speech recognition services. Given t…