IEEE Automatic Speech Recognition and Understanding Workshop · 2011 · 264 citations · 16 references
ComputingComputer ScienceComputational LinguisticsNatural Language ProcessingTranslator TrainingDeep LearningLanguage ModelingLanguage ModelsMachine TranslationSpeech RecognitionNeural Language ModelsNeural Machine TranslationOptimal Parameter TuningParameter SelectionRecurrent Neural Language ModelsRecurrent Neural Network Language ModelsRecurrent Neural NetworksSpeech-to-text Translation
We present a freely available open-source toolkit for training recurrent neural network based language models. It can be easily used to improve existing speech recognition and machine translation systems. Also, it can be used as a baseline for future research of advanced language modeling techniques. In the paper, we discuss optimal parameter selection and different modes of functionality. The toolkit, example scripts and basic setups are freely available at http://rnnlm.sourceforge.net/.
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