LSTM Language Model Adaptation with Images and Titles for Multimedia Automatic Speech Recognition

@article{Moriya2018LSTMLM,
  title={LSTM Language Model Adaptation with Images and Titles for Multimedia Automatic Speech Recognition},
  author={Yasufumi Moriya and G. Jones},
  journal={2018 IEEE Spoken Language Technology Workshop (SLT)},
  year={2018},
  pages={219-226}
}
  • Yasufumi Moriya, G. Jones
  • Published 1 December 2018
  • Computer Science
  • 2018 IEEE Spoken Language Technology Workshop (SLT)
Transcription of multimedia data sources is often a challenging automatic speech recognition (ASR) task. [] Key Method Our language model is tested on transcription of an existing corpus of instruction videos and on a new corpus consisting of lecture videos. Consistent reduction in perplexity by 5–10 is observed on both datasets. When the non-adapted model is combined with the image adaptation and video title adaptation models for n-best ASR hypotheses re-ranking, additionally the word error rate (WER) is…

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