{'fraction_non_alphanumeric': 0.018218623481781375, 'fraction_numerical': 0.005398110661268556, 'mean_word_length': 5.337606837606837, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Indonesian natural voice command for robotic applications

Human-machine interaction has been growing with the discovery of artificial intelligence technology. The development of human-machine interaction leads to a more natural interaction. In daily interactions, human uses speech, more dominant than the other way such as gestures and eye contact. Speech is the vocalized form of human communication which is closely related to language system. The problem is meaning, ambiguity, and the language that is not according to the rules of syntax, causing the command translation become more complex. To understand the meaning of the voice command, it is necessary to know the semantic and syntactic structure of sentences. An artificial intelligence technology that can understand Indonesian voice commands for robotic applications will be developed in this research. The purpose of this research is to translate voice command into the robots action, to generate human-machine interaction more natural. The voice command will be extracted using bark-frequency cepstral coefficients. Cepstral identified into words using neural networks. Words in a complete sentences will be processed using natural language processing so that, the meaning and appropriate action from the given command can be executed. Speech recognition experiments with 28 sets of speech signal obtain 82 % accuracy, while natural language processing experiments obtain 93 % accuracy with 50 sets of learning data.