Speech Encoder Recognition Algorithm Based on Deep Learning

The speech coding data of different types of speech coding has potential heterogeneous features, and there are linear or nonlinear correlations among the heterogeneous features, so it is necessary to use artificial intelligence methods to dig deeply so as to carry out intelligent classification of speech coding features. Because different speech encoders use different compression algorithms, they will have different effects on speech, and these effects will change significantly after the speech signal is decoded. Therefore, how can we effectively identify the encoding mode to judge which decoding mode is particularly important? This paper will use artificial intelligence technology and deep learning to realize speech coding type recognition technology based on the speech coding feature extraction method, which can carry out differential analysis of speech data of different coding types, analyze and summarize its features, and complete feature analysis and recognition of common speech coding.