Audio content generation and classification

A method, comprising:

• receiving, by a control system, first audio data of a first audio data format including one or more first audio signals and associated first spatial data, wherein the first spatial data indicates intended perceived spatial positions for the one or more first audio signals;
• determining, by the control system, at least a first feature type from the first audio data, wherein the first feature type corresponds to a frequency domain representation of the audio data;
• applying, by the control system, a positional encoding process to the first audio data, to produce first encoded audio data, the first encoded audio data including representations of at least the first spatial data and the first feature type in first embedding vectors of an embedding dimension;
• receiving, by the control system, second audio data of a second audio data format including one or more second audio signals and associated second spatial data, the second audio data format being different from the first audio data type, wherein the second spatial data indicates intended perceived spatial positions for the one or more second audio signals;
• determining, by the control system, at least the first feature type from the second audio data;
• applying, by the control system, the positional encoding process to the second audio data, to produce second encoded audio data, the second encoded audio data including representations of at least the second spatial data and the first feature type in second embedding vectors of the embedding dimension;
• and
• training a neural network implemented by the control system to identify an input audio data type of input audio data, wherein identifying the input audio data type involves identifying a content type of the input audio data, the training being based, at least in part, on the first encoded audio data and the second encoded audio data.