@techreport{TD:100444,
	att_abstract={{Word error rate (WER), which is the most commonly used method of measuring automatic speech recognition (ASR) accuracy,
penalizes all ASR errors (insertions, deletions, substitutions) equally.
However, humans differentially weigh different types of ASR errors. They judge ASR errors that distort the meaning of the spoken message more harshly than those that do not.
Following the central idea of differential weighting of different ASR errors, we developed a new metric, HPA (Human Perceived Accuracy) that aims to align more closely with human perception of ASR errors. Applied to the particular task of automatically recognizing voicemails, we found that the correlation between HPA and the human perception of ASR accuracy was significantly higher (r-value=0.91) than the correlation between WER and human judgement (r-value=0.65).}},
	att_authors={tm330a, al1649, mg1528},
	att_categories={C_IIS.11},
	att_copyright={{ISCA}},
	att_copyright_notice={{The definitive version was published in Interspeech. {{, 2011-08-28}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:100444},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100444_DS1_2011-04-05T14:35:55.473Z.pdf},
	author={Taniya Mishra and Andrej Ljolje and Mazin Gilbert},
	institution={{Interspeech}},
	month={August},
	title={{Predicting Human Perceived Accuracy of ASR Systems}},
	year=2011,
}