MUMBAI, India, Aug. 8 -- Intellectual Property India has published a patent application (202517063975 A) filed by Google Llc, Mountain View, U.S.A., on July 4, for 'diffusion models for generation of audio data based on descriptive textual prompts.'

Inventor(s) include Huang, Qingqing; Han, Wei; Park, Daniel Sung-Joon; Jansen, Aren; Li, Yue; Lee, Joonseok; Ellis, Dan; Wang, Tao; Denk, Timo Immanuel; and Ganti, Ravi.

The application for the patent was published on Aug. 8, under issue no. 32/2025.

According to the abstract released by the Intellectual Property India: "A corpus of textual data is generated with a machine-learned text generation model. The corpus of textual data includes a plurality of sentences. Each sentence is descriptive of a type of audio. For each of a plurality of audio recordings, the audio recording is processed with a machine-learned audio classification model to obtain training data including the audio recording and one or more sentences of the plurality of sentences closest to the audio recording within a joint audio-text embedding space of the machine-learned audio classification model. The sentence(s) are processed with a machine- learned generation model to obtain an intermediate representation of the one or more sentences. The intermediate representation is processed with a machine-learned cascaded diffusion model to obtain audio data. The machine-learned cascaded diffusion model is trained based on a difference between the audio data and the audio recording. In a computing system, the machine-learned generator is used to generate intermediate representations of textual content corresponding a query descriptive of a user desired type of audio content, the machine-learned diffusion model is used to obtain audio data based on the intermediate representation of textual content, the obtained audio data comprises audio of the desired type of audio content."

The patent application was internationally filed on Jan. 26, 2024, under International application No.PCT/US2024/013191.

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