Voice wakeup method and apparatus, storage medium, and system

A voice wakeup apparatus, wherein the apparatus comprises:

• a processor;
• and
• a memory, configured to store instructions to be executed by the processor, wherein
• upon executing the instructions, the processor is configured to implement the following:
• obtaining first microphone data;
• performing first-stage processing based on the first microphone data to obtain first wakeup data, wherein the first-stage processing comprises first-stage separation processing and first-stage wakeup processing that are based on a neural network model;
• wherein the first wakeup data comprises a first confidence level, and the first confidence level indicates a probability that the first microphone data comprises a preset wakeup keyword which comprises N wakeup keywords, wherein N is a natural number;
• wherein the first confidence level is an (N+1) dimensional vector in which N dimensions correspond to the N wakeup keywords;
• and based on the first confidence level being greater than a first threshold, the first wakeup data indicates that a pre-wakeup succeeds;
• performing second-stage processing according to the first microphone data to obtain second wakeup data, based on the first wakeup data indicating that the pre-wakeup succeeds, wherein the second-stage processing comprises second-stage separation processing and second-stage wakeup processing that are based on the neural network model;
• and
• determining a wakeup result based on the second wakeup data.

A non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer program instructions, and upon the computer program instructions being executed by a processor, the processor is configured to implement the following:

• obtaining first microphone data;
• performing first-stage processing based on the first microphone data to obtain first wakeup data, wherein the first-stage processing comprises first-stage separation processing and first-stage wakeup processing that are based on a neural network model;
• wherein the first wakeup data comprises a first confidence level, and the first confidence level indicates a probability that the first microphone data comprises a preset wakeup keyword which comprises N wakeup keywords, wherein N is a natural number;
• wherein the first confidence level is an (N+1) dimensional vector in which N dimensions correspond to the N wakeup keywords;
• and based on the first confidence level being greater than a first threshold, the first wakeup data indicates that a pre-wakeup succeeds;
• performing second-stage processing according to the first microphone data to obtain second wakeup data, based on the first wakeup data indicating that the pre-wakeup succeeds, wherein the second-stage processing comprises second-stage separation processing and second-stage wakeup processing that are based on the neural network model;
• and
• determining a wakeup result based on the second wakeup data.