Recognition of spontaneous conversational speech using long short-term memory phoneme predictions

@inproceedings{Wllmer2010RecognitionOS,
  title={Recognition of spontaneous conversational speech using long short-term memory phoneme predictions},
  author={Martin W{\"o}llmer and Florian Eyben and Bj{\"o}rn W. Schuller and Gerhard Rigoll},
  booktitle={INTERSPEECH},
  year={2010}
}
We present a novel continuous speech recognition framework designed to unite the principles of triphone and Long ShortTerm Memory (LSTM) modeling. The LSTM principle allows a recurrent neural network to store and to retrieve information over long time periods, which was shown to be well-suited for the modeling of co-articulation effects in human speech. Our system uses a bidirectional LSTM network to generate a phoneme prediction feature that is observed by a triphone-based large-vocabulary… CONTINUE READING
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