Abstract
This paper describes the implementation of voice conversion system using linear prediction coefficients (LPC) and artificial neural networks (ANN). In this work, microphone recorded parallel speech utterances are used for voice conversion. Linear prediction coefficients are extracted from the speech utterance of the source and target speakers using linear prediction analysis. Auto associative neural networks (AANN) are configured and used for the transformation of LP coefficients from the source speaker to target speaker. LP residual obtained from target speaker and transformed LP coefficients are used to reconstruct the transformed speech. Mean opinion score and student t-test tests are conducted to evaluate the performance of voice conversion system. Evaluation of voice conversion system is performed in all 4 cases; such as male-to-male, male-to-female, female-to male and female-to-female. The test results show that the quality of transformed speech is good and AANN's have properly transformed LP coefficients of the source to that target speaker.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.