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User adaptation of input-response pairs in an example-based dialog system using distributed representation of words

机译:使用单词的分布式表示的基于示例的对话框系统中的用户对输入响应对的适应

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There is a need to develop spoken dialog systems, such as chatbots, which are capable of engaging in natural conversations with people, especially the socially isolated elderly. We propose an example-based dialog system featuring an adaptation method which customizes the dialog for each user. After retrieving profile information about the user from the Web, morpheme analysis is applied to the retrieval results and only nouns and proper nouns are extracted. Those which appear with high frequency are considered to be related to the user. We then calculate the similarity between the selected words related to the user and words in the existing example phrases of the dialog system. Cosine similarity between the distributed representations of the nouns is calculated using the word2vec program. We then generate phrases adapted to the user by substituting user-related words for highly similar words in the original example phrases. We manually evaluated the naturalness of the generated phrases and found that the system could generate natural-sounding phrases. Word2vec has a special property which allows arithmetic operations such as plus and minus to be applied to distributed word representations. Using this feature, we were able to derive replacement of words for the example phrases by applying operations to the words used in the original phrases, improving the success rate for generating natural-sounding phrases.
机译:需要开发诸如聊天机器人之类的口语对话系统,其能够与人们,特别是与社会隔绝的老年人进行自然对话。我们提出了一个基于示例的对话框系统,该系统具有一种适应方法,可以为每个用户定制对话框。从Web检索有关用户的个人资料信息后,将词素分析应用于检索结果,并且仅提取名词和专有名词。那些出现频率高的那些被认为与用户有关。然后,我们计算与用户相关的所选单词与对话系统现有示例短语中的单词之间的相似度。使用word2vec程序计算名词的分布式表示形式之间的余弦相似度。然后,通过用用户相关的单词替换原始示例短语中的高度相似的单词,我们生成适合用户的短语。我们手动评估了生成短语的自然性,发现系统可以生成听起来自然的短语。 Word2vec具有一个特殊的属性,该属性允许将算术运算(例如加号和减号)应用于分布式字词表示形式。使用此功能,我们可以通过对原始短语中使用的单词进行操作,从而导出示例短语的单词替换,从而提高了生成自然发音短语的成功率。

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