Acoustic event detecting method under hospital noise environment

Abstract

The invention relates to an acoustic event detecting method, in particular to an acoustic event detecting method under the hospital noise environment. According to the acoustic event detecting methodunder the hospital noise environment, voice is accurately recognized to be text, the recognition rate of an electronic medical record input through the voice is increased, and the false recognition rate is decreased. The acoustic event detecting method comprises the following steps that 1, feature intercepting is conducted on an audio signal of each acoustic event, and audio clips of the audio signals are marked correspondingly; 2, an MFCC feature coefficient of each target acoustic event in audio is extracted; 3, voice phonemes are aligned; 4, feature matrixes of the voice are generated; 5, aCRNN model is established for each target acoustic event; 6, the audio signals of the to-be-detected target acoustic events collected in real time under the hospital noise environment are pre-processed, and then MFCC feature extraction is conducted; 7, the category of the to-be-detected target acoustic events is obtained; and 8, the audio clips irrelevant to the target acoustic events are filed out.

Description

technical field [0001] The invention relates to an acoustic event detection method, in particular to an acoustic event detection method in a hospital noise environment. Background technique [0002] The recognition rate of existing voice electronic medical records will drop significantly when the signal-to-noise ratio is very low, or when multiple people are speaking. Therefore, acoustic event detection becomes a key step in how to remove the influence of noise in the hospital environment. [0003] The current speech recognizer classifies non-speech into one category: noise. In fact, noise in reality may be more complex than speech. If it can also model various types of noise, it will help speech recognition to distinguish which ones. It is a useful voice, which has great significance for the recognition of voice electronic medical records. Contents of the invention [0004] The present invention aims at the defects existing in the prior art, and provides an acoustic even...

AI Technical Summary

Problems solved by technology

[0002] The recognition rate of existing voice electronic medical records will drop significantly when the signal-to-noise ratio is very low, or when multiple people are speaking. Therefore, acoustic event detection becomes a key step in how to remove the influence of noise in the hospital environment.

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