Acoustic network model training method and device and electronic equipment

Abstract

The embodiment of the invention provides an acoustic network model training method and device and electronic equipment, and belongs to the technical field of data processing, and the method comprisesthe steps: obtaining a training sample for the training of an acoustic network model, and enabling the training sample to comprise one or more voice files; performing peak detection on voice containedin the voice file by using a BLSTM network so as to divide letters contained in the voice file based on the detected peak to form segmented voice; performing semantic prediction on the segmented voice based on a preset CTC segmentation network to obtain a text prediction result; and after the prediction result meets a preset performance requirement, stopping training the acoustic network model soas to carry out character prediction on the input voice by using the acoustic network model. Through the processing scheme of the invention, the training efficiency of the acoustic network model canbe improved.

Description

technical field [0001] The present disclosure relates to the technical field of data processing, and in particular to an acoustic network model training method, device and electronic equipment. Background technique [0002] Speech processing (Speech processing), also known as voice signal processing, human voice processing, its purpose is to make the desired signal, further do voice recognition, apply to the mobile phone interface and even ordinary life, so that people and computers can communicate. [0003] In the process of speech processing, the audio-like sound signal received by a microphone or other devices can be used to process the data through an analog-to-digital conversion device, and finally output through a digital-to-analog conversion device. Therefore, the processing is for digital signals, and the speech signal is a discrete time signal. The signal processing flow is as follows: Collect and sample signals: use a microphone or various radio devices to collect...

AI Technical Summary

Problems solved by technology

The signal processing flow is as follows: Collect and sample signals: use a microphone or various radio devices to collect analog voice signals, and then use an ADC device (such as an analog-to-digital conversion card) to convert the analog signal into a digital signal, and then according to the Nyquist theory For sampling, if it does not conform to the theory, it will cause signal distortion

Images