@InProceedings{mirzaei-meshgi-kawahara:2016:CL4LC,
  author    = {Mirzaei, Maryam Sadat  and  Meshgi, Kourosh  and  Kawahara, Tatsuya},
  title     = {Automatic Speech Recognition Errors as a Predictor of L2 Listening Difficulties},
  booktitle = {Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {192--201},
  abstract  = {This paper investigates the use of automatic speech recognition (ASR) errors as
	indicators of the second language (L2) learners' listening difficulties and in
	doing so strives to overcome the shortcomings of Partial and Synchronized
	Caption (PSC) system. PSC is a system that generates a partial caption
	including difficult words detected based on high speech rate, low frequency,
	and specificity. To improve the choice of words in this system, and explore a
	better method to detect speech challenges, ASR errors were investigated as a
	model of the L2 listener, hypothesizing that some of these errors are similar
	to those of language learners' when transcribing the videos. To investigate
	this hypothesis, ASR errors in transcription of several TED talks were analyzed
	and compared with PSC's selected words. Both the overlapping and mismatching
	cases were analyzed to investigate possible improvement for the PSC system.
	Those ASR errors that were not detected by PSC as cases of learners'
	difficulties were further analyzed and classified into four categories:
	homophones, minimal pairs, breached boundaries and negatives. These errors were
	embedded into the baseline PSC to make the enhanced version and were evaluated
	in an experiment with L2 learners. The results indicated that the enhanced
	version, which encompasses the ASR errors addresses most of the L2 learners'
	difficulties and better assists them in comprehending challenging video
	segments as compared with the baseline.},
  url       = {http://aclweb.org/anthology/W16-4122}
}