Speech recognition-based iterative denoising device and cleaning robot

Abstract

The invention discloses a speech recognition-based iterative denoising device and a cleaning robot. The iterative denoising device comprises a confidence coefficient value acquiring unit, a pre-de-noising unit, and a processing unit; the confidence coefficient value acquiring unit is used for determining target speech signals from speech signals acquired by a microphone array, and obtaining a target confidence coefficient value accordingly; the pre-de-noising unit is used for receiving the target confidence coefficient value obtained by the confidence coefficient value acquiring unit, and selecting noise data matching the target confidence coefficient value from a noise database, and then controlling the noise data and unmarked sound frames in the target speech signals to be subjected to pre-de-noising processing so as to obtain a pre-de-noising processing result corresponding to the noise data; and the processing unit is used for adjusting the target confidence coefficient value according to a relationship between the pre-de-noising processing result outputted by the pre-no-noising unit and a predetermined threshold value, and transmitting the adjusted result to the pre-de-noisingunit so as to achieve denoising processing on the unmarked sound frames.

Description

technical field [0001] The invention belongs to the technical field of robots, and in particular relates to a speech recognition-based iterative denoising device and a cleaning robot. Background technique [0002] Existing mobile robots (such as mechatronics equipment such as sweeping robots, window cleaning robots, and floor mopping robots among cleaning robots) will generate noise during work. The voice signal is picked up by voice, but when the voice signal from the user is picked up, the noise generated during the robot's work is usually picked up by voice, so that the voice signal picked up by the device is mixed with a lot of external noise , the corresponding speech recognition accuracy is not high, which will seriously affect the robot's recognition of external speech (effective signal), and make logical decisions based on speech interpretation (such as performing relevant path planning). [0003] In the prior art, the method of denoising at the front end of the voi...

AI Technical Summary

Problems solved by technology

[0002] Existing mobile robots (such as mechatronics equipment such as sweeping robots, window cleaning robots, and floor mopping robots among cleaning robots) will generate noise during work. The voice signal is picked up by voice, but when the voice signal from the user is picked up, the noise generated during the robot's work is usually picked up by voice, so that the voice signal picked up by the device is mixed with a lot of external noise , the corresponding voice recognition accuracy is not high, which will seriously affect the robot's recognition of external voices (effective signals), and make logical decisions based on voice interpretation (such as performing relevant path planning)

[0003] In the prior art, the method of denoising at the front end of the voice signal is generally to select the appropriate voice signal according to the result of the voice signal classification, and suppress the voice signal that does not meet the requirements, but the method for the voice signal classification is more complicated, not only The noise reduction is not complete, and the efficiency of speech recognition is not high, there are always remaining speech frames that have not been processed, which affects the effect of speech recognition

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