Author: Zen and the Art of Computer Programming
With the rapid development of technology, smartphones have gradually become one of the main tools for popularization. Smartphones have irreplaceable advantages in serving consumers, but they also bring new challenges. Such a huge market leads to a huge information gap between users and service providers, and users have higher and higher requirements for the service quality of customer service personnel. Customer service personnel solve users' problems by directly contacting customers, but this method consumes a lot of time and energy for users. Therefore, how to establish an intelligent customer service system to help users obtain satisfactory services quickly and conveniently is an important goal of the customer service system. At present, there are many intelligent customer service system products on the market, but most of them are based on speech recognition technology, but it is difficult to meet today's needs. Therefore, we hope to apply speech recognition technology to the intelligent customer service system through research and practice, so as to improve customer experience, reduce response time and improve customer satisfaction.
2. Explanation of basic concepts and terms
2.1 Speech Recognition
Speech recognition (Speech Recognition) refers to the process of converting human voice or speech into text or instructions that computers can understand. Speech recognition generally uses natural language processing methods, that is, using computers to simulate the pronunciation rules of human intonation, tone, wording, etc. to process speech signals, so as to perform speech recognition. Speech recognition systems are divided into three types: end-to-end, semi-end-to-end, and hybrid models.
2.1.1 Pronunciation Rules
Pronunciation rules refer to the rules formulated by computer simulation of human pronunciation habits. Specifically including initials, finals, prosody, etc., which are the basis for the speech recognition system to analyze sounds.
2.1.2 Language Model
A language model is a probabilistic statistical model that is used to describe the likelihood of a sentence appearing. The language model uses statistical methods to assign a probability to each word in a piece of text, and accumulates these probabilities according to certain rules to obtain the probability distribution of the entire text.
2.1.3 Acoustic model
The acoustic model refers to the root