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Towards the creation of reliable voice control system based on a fuzzy approach

机译:基于模糊方法的可靠语音控制系统的建立

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The key purpose of this paper is to train a voice control system if a small amount of user speech data is available without need for general acoustic model if the latter does not fit to the user voice due to known variability sources (childhood, voice diseases, non nativeness, etc.). We explore the possibility to increase the recognition rate by requiring the speaker to put the stress on all vowels in a command. We propose the novel modification of our fuzzy phonetic decoding method, in which each vowel is put in correspondence with a fuzzy union of sets of available reference signals from this class. A first, syllables are detected and phoneme segmentation is performed. Secondly, the command is extracted from spontaneous speech by thresholding the ratio of the duration of homogeneous segments to the duration of the whole syllable. Finally, each syllable is put in correspondence with the fuzzy set of vowels, and commands are ordered based on similarity with the fuzzy set of the utterance. The experimental results in synthetic and real Russian datasets prove that our method is characterized by better accuracy in comparison with known recognition methods. (C) 2015 Elsevier B.V. All rights reserved.
机译:本文的主要目的是训练语音控制系统,如果有少量的用户语音数据可用,而无需通用声学模型,如果后者由于已知的可变性源(儿童,语音疾病,非本地性等)。我们探索了通过要求说话者在命令中对所有元音施加压力来提高识别率的可能性。我们提出了模糊语音解码方法的新颖修改,其中每个元音都与该类可用参考信号集的模糊联合相对应。首先,检测音节并执行音素分割。其次,通过对同构片段的持续时间与整个音节的持续时间之比设定阈值,从自发语音中提取命令。最后,将每个音节与元音的模糊集相对应,并基于与发声的模糊集的相似性对命令进行排序。在合成的和真实的俄罗斯数据集中的实验结果证明,与已知的识别方法相比,我们的方法具有更好的准确性。 (C)2015 Elsevier B.V.保留所有权利。

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