Speech recognition and semantic recognition each play an important role in artificial intelligence technology, and there are obvious differences between them.

Speech recognition is a kind of perceptual intelligence technology, its main task is to convert the speech signal in the audio into the corresponding text. In other words, speech recognition technology is concerned with how to accurately transcribe sound into text, without involving the understanding of the text content. For example, the speech-to-text function in the input method is the application of speech recognition technology.

In contrast, semantic recognition (or semantic understanding) falls under the category of cognitive intelligence. It is not just about the words themselves, but more importantly about understanding the meaning and intent of the content and responding to it. Semantic recognition technology can analyze the information in the text, identify the user's intention, emotion, theme, etc., so as to provide users with more intelligent services. For example, when the user says "a love movie" or "hot action movie" and other vague statements in front of the TV, the TV can perform intelligent analysis according to the user's gender, hobbies, and usual on-demand tendency, and recommend the corresponding movie, which is the application of semantic recognition.

Therefore, speech recognition and semantic recognition have their respective focuses in artificial intelligence technology. Speech recognition mainly solves the transcription problem of sound to text, while semantic recognition is more focused on understanding the meaning and intention of text content, and providing intelligent services for users. In practical applications, the two often need to be combined to achieve a more natural and efficient human-computer interaction.