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A voice command detection system for aerospace applications

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Abstract

Nowadays, according to ever-increasing volumes of audio content, audio processing is a vital need. In the aerospace field, voice commands could be used instead of data commands in order to speed up the command transmission, help crewmembers to complete their tasks by allowing hands-free control of supplemental equipment and as a redundant system for increasing the reliability of command transmission. In this paper, a voice command detection (VCD) framework is proposed for aerospace applications, which decodes the voice commands to comprehensible and executable commands, in an acceptable speed with a low false alarm rate. The framework is mainly based on a keyword spotting method, which extracts some pre-defined target keywords from the input voice commands. The mentioned keywords are input arguments to the proposed rule-based language model (LM). The rule-based LM decodes the voice commands based on the input keywords and their locations. Two keyword spotters are trained and used in the VCD system. The phone-based keyword spotter is trained on TIMIT database. Then, speaker adaptation methods are exploited to modify the parameters of the trained models using non-native speaker utterances. The word-based keyword spotter is trained on a database prepared and specialized for aerospace applications. The experimental results show that the word-based VCD system decodes the voice commands with true detection rate equal to 88% and false alarm rate equal to 12%, in average. Additionally, using speaker adaptation methods in the phone-based VCD system improves the true detection and false alarm rates about 21% and 21%, respectively.

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Authors and Affiliations

  1. Aerospace Research Institute, Ministry of Science, Research and Technology, Aerospace Research Center Lane, Mahestan Street, Iran Zamin Street, Tehran, 14657-74111, Iran

    Shima Tabibian

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  1. Shima Tabibian
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Correspondence to Shima Tabibian.

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Tabibian, S. A voice command detection system for aerospace applications. Int J Speech Technol 20, 1049–1061 (2017). https://doi.org/10.1007/s10772-017-9467-4

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