Deep learning-based intelligent industrial robot speech interaction and control method

Abstract

The invention discloses a deep learning-based intelligent industrial robot speech interaction and control method. The method comprises the following steps that: 1) speech is converted into a speech spectrum: original speech is converted into an image through FFT (Fast Fourier Transformation), wherein the image can be used as input; 2) modeling is performed on the whole speech sentence: the speech spectrum, adopted as input, is utilized to perform unsupervised training on a convolutional neural network; 3) the output sequence O of the convolutional neural network is compared with a tag T, and the convolutional neural network is adjusted in a supervised manner through the BP algorithm; and 4) specific text information is inputted into a robot as a control command. According to the deep learning-based intelligent industrial robot speech interaction and control method of the invention, the speech recognition technology and the industrial robot are combined together, and therefore, a traditional production mode is changed, the labor intensity of workers is decreased, labor productivity is enhanced, and the intelligentization development of industrial technologies can be promoted.

Description

technical field [0001] The invention relates to the technical field of deep learning and voice control of industrial robots, in particular to a voice interaction and control method for intelligent industrial robots based on deep learning. Background technique [0002] For a long time, speech, as a unique human ability, is the most essential difference between humans and other animals, and it is also the most important tool and channel for humans to communicate and obtain external information resources. The 21st century is an era of vigorous development of information technology. Speech recognition technology, as an important component of the human-computer interaction branch in this torrent, is an important interface for human-computer interaction, making the interaction between humans and machines more automated and intelligent, and realizing the machine. The main way to understand human language has promoted the development of artificial intelligence. Therefore, the combi...

AI Technical Summary

Problems solved by technology

[0004] In recent years, with the upsurge of deep learning rising again, the research on the speech recognition system based on deep neural network has been hot. At present, the best speech recognition system uses a bidirectional long short-term memory network (LSTM, Long Short Term Memory), but this Due to the high complexity of system training and long decoding time, it is difficult to be widely used in industrial real-time recognition systems, especially in the environment of huge noise in factories.

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