DMCA
ASR Satisficing: The effects of ASR accuracy on speech retrieval (2000)
| Citations: | 22 - 5 self |
BibTeX
@MISC{Stark00asrsatisficing:,
author = {Litza Stark and Steve Whittaker and Julia Hirschberg},
title = {ASR Satisficing: The effects of ASR accuracy on speech retrieval},
year = {2000}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
We examine how differences in the accuracy of Automatic Speech Recognition transcripts affect users' ability to use these in tasks requiring the retrieval of speech "documents". We compare performance measures, processing strategies, and preference data for subjects using transcripts and speech data to perform a series of relevance judgment and summary tasks on transcripts with different levels of accuracy. Results show effects for transcript quality on solution accuracy, time to solution, amount of speech played for the task, likelihood of subjects abandoning use of a transcript, and subject perceptions of task difficulty, transcript utility, readability, and comprehensibility. 1. INTRODUCTION Research on Automatic Speech Recognition (ASR) generally assumes perfect transcription accuracy to be its holy grail. The more accurately a system can transcribe an utterance, the better that system performs (modulo time factors) Recently this assumption is being challenged, however. Different...
Keyphrases
asr satisficing speech retrieval asr accuracy summary task automatic speech recognition transcript speech document automatic speech recognition holy grail system performs preference data transcript utility speech data different level transcript quality modulo time factor performance measure perfect transcription accuracy task difficulty solution accuracy subject perception introduction research relevance judgment
