Internet of Things voice compression and decompression method

Abstract

The invention discloses an Internet of Things voice compression and decompression method, and belongs to the field of voice data, and the method comprises the steps: continuously intercepting voice data with the total time length of t in real time, then taking points from the voice data according to the interval time of t / 2n, and taking 2n points as the Nth frame of data; performing high-frequency pre-emphasis on the Nth frame of data, converting time domain data into frequency domain data, performing modulus calculation on a power spectrum to obtain a frequency spectrum, selecting each harmonic amplitude in the frequency spectrum, and performing calculation by using each harmonic amplitude to obtain a total attenuation coefficient; dividing each harmonic amplitude by the total attenuation coefficient to obtain an amplitude ratio of each harmonic; combining the Nth frame of data with the frequency spectrum to carry out fundamental wave analysis to obtain a fundamental wave frequency value; and arranging the fundamental wave frequency value, each harmonic amplitude ratio and the total attenuation coefficient to generate a transmission sequence code column. The voice compression method is strong in real-time performance and high in compression rate, and can be similar to a communication effect of making a call.

Description

[0001] This application is a divisional application of an invention patent application with an application date of January 29, 2019, titled "Method for Real-time Voice Compression and Decompression for Narrowband Internet of Things", and application number 201910086356.4. technical field [0002] The present invention relates to the technical field of voice communication in the narrowband Internet of Things, more specifically, to a voice compression and decompression method of the Internet of Things, and an application in walkie-talkies. Background technique [0003] With the explosive development of information technology, today's world has entered the era of the Internet of Everything, and various Internet of Things technologies emerge in endlessly. However, due to the inherent narrow bandwidth, low transmission rate and long delay of NB-IoT. As a result, there are great difficulties in transmitting voice signals using communication methods such as Zigbee, LoRa, and NB-IOT...

AI Technical Summary

Problems solved by technology

However, due to the inherent narrow bandwidth, low transmission rate and long delay of NB-IoT

As a result, there are great difficulties in transmitting voice signals using communication methods such as Zigbee, LoRa, and NB-IOT. How to effectively use the limited bandwidth resources of the narrowband Internet of Things to realize voice transmission and reception with a data volume of more than 22KB / s has become an urgent need solved problem

[0004] 1. Take LoRa as an example: when using LoRa technology to transmit data, if the transmitted code rate is less than 8B / s, the transmission distance can reach 25 kilometers (open space), and when the code rate reaches 960B / s, under the same conditions The transmission distance has dropped below 1Km, and the data volume of general voice communication reaches 22KB / s. Under uncompressed conditions, it is basically impossible to transmit through LoRa

[0005] 2. The theoretical bandwidth of Zigbee is 256KB / s, but the data packets of various protocols in the transmitted data actually occupy a large proportion, and the bandwidth that can be reserved for voice communication is very limited. If it is not suitable for voice data up to 22KB / s Compression, even if Zigbee can barely transmit, it will bring a lot of delay

[0007] (1) The real-time performance is not strong: MPEG2 needs to sample at least one complete voice syllable data before the compressed data is enough to ensure the quality of the call, and a complete syllable is at least 0.4-0.7s long, plus the call time Delay, usually the total call delay is at least 1s, and our real-time voice compression technology completes one frame compression every 50ms, so the real-time nature of the call is much stronger than MPEG2

[0008] (2) Insufficient compression ratio: the compression ratio of MPEG2 is 12:1--10:1, and the insufficient compression ratio cannot be used in real-time voice transmission technology in the narrowband Internet of Things

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