Word neighborhoods have been suggested but not thoroughly explored as an explanatory variable for errors in automatic speech recognition (ASR). We revisit the definition of word neighborhoods, propose new measures using a fine-grained articulatory representation of word pronunciations, and consider new neighbor weighting functions. We analyze the significance of our measures as predictors of errors in an isolated-word ASR system and a continuous-word ASR system. We find that our measures are significantly better predictors of ASR errors than previously used neighborhood density measures.
['Preethi Jyothi', 'Karen Livescu']
Revisiting Word Neighborhoods for Speech Recognition