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Deep Learning for Natural Language Processing and Language Modelling

机译:用于自然语言处理和语言建模的深度学习

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The article presents an example of practical application of deep learning methods for language processing and modelling. Development of statistical language models helps to predict a sequence of recognized words and phonemes, and can be used for improving speech processing and speech recognition. However, currently the field of language modelling is shifting from statistical language modelling methods to neural networks and deep learning methods. Therefore, one of the methods of effective language modelling with the use of deep learning techniques is presented in this paper. Presented results concerns the modelling of the Polish language but the achieved research results and conclusions can also be applied to language modelling application for other languages.
机译:本文提供了一个深度学习方法在语言处理和建模中的实际应用示例。统计语言模型的开发有助于预测已识别单词和音素的序列,并可用于改善语音处理和语音识别。然而,当前语言建模领域正在从统计语言建模方法转变为神经网络和深度学习方法。因此,本文提出了一种利用深度学习技术进行有效语言建模的方法。提出的结果涉及波兰语言的建模,但是所获得的研究结果和结论也可以应用于其他语言的语言建模应用。

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