View source for US Patent Application 17826987. TECHNIQUES FOR IMPROVED ZERO-SHOT VOICE CONVERSION WITH A CONDITIONAL DISENTANGLED SEQUENTIAL VARIATIONAL AUTO-ENCODER simplified abstract

=TECHNIQUES FOR IMPROVED ZERO-SHOT VOICE CONVERSION WITH A CONDITIONAL DISENTANGLED SEQUENTIAL VARIATIONAL AUTO-ENCODER=


==Organization Name==

[[:Category:Tencent America LLC|Tencent America LLC]]


[[Category:Tencent America LLC]]

==Inventor(s)==

[[:Category:Chunlei Zhang of Bellevue WA (US)|Chunlei Zhang of Bellevue WA (US)]][[Category:Chunlei Zhang of Bellevue WA (US)]]

[[:Category:Jiachen Lian of Palo Alto CA (US)|Jiachen Lian of Palo Alto CA (US)]][[Category:Jiachen Lian of Palo Alto CA (US)]]

[[:Category:Dong Yu of Palo Alto CA (US)|Dong Yu of Palo Alto CA (US)]][[Category:Dong Yu of Palo Alto CA (US)]]

==TECHNIQUES FOR IMPROVED ZERO-SHOT VOICE CONVERSION WITH A CONDITIONAL DISENTANGLED SEQUENTIAL VARIATIONAL AUTO-ENCODER - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17826987 titled 'TECHNIQUES FOR IMPROVED ZERO-SHOT VOICE CONVERSION WITH A CONDITIONAL DISENTANGLED SEQUENTIAL VARIATIONAL AUTO-ENCODER

==Simplified Explanation==

- The patent application describes a method for voice conversion using a conditional disentangled sequential variational auto-encoder (C-DSVAE).
- The method involves receiving input speech segments and encoding them using a shared encoder to generate a speaker embedding and a content embedding.
- The speaker embedding and content embedding are further encoded using separate encoders to obtain encoded results.
- A content bias is enabled, and the content embedding is reshaped using the content bias.
- Finally, a reconstructed speech output is generated based on the encoded results and the reshaped content embedding.


==Original Abstract Submitted==

A method, system, apparatus, and computer-readable medium for voice conversion using a conditional disentangled sequential variational auto-encoder (C-DSVAE) is provided. The method, performed by at least one processor, includes receiving input speech segments, encoding the input speech segments via a shared encoder to generate a speaker embedding and a content embedding, and encoding a posterior distribution of the speaker embedding via a speaker encoder and encoding a posterior distribution of the content embedding via a content encoder to obtain encoded results. The method further includes enabling a content bias, reshaping the content embedding using the content bias, and generating a reconstructed speech output based on the encoded results and the reshaped content embedding.



[[Category:G10L19/00]]