ESPnet: End-to-end speech processing toolkit

You can learn more about ESPnet at our upcoming online meetup on May 25 6:00 pm CET.

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Shinji Watanabe (CMU): ESPnet – End-to-end speech processing toolkit

An end-to-end neural approach has become a popular alternative to conventional modular approaches in various speech applications, including speech recognition and synthesis. One of the benefits of this end-to-end neural framework is that we can use a unified framework for different speech processing problems based on sequence-to-sequence modeling and tightly integrate these problems in a joint training manner. This talk introduces various end-to-end speech processing applications by focusing on the above-unified framework and several integrated systems (e.g., speech recognition and synthesis, speech separation and recognition, speech recognition and translation) implemented within an open-source toolkit named ESPnet (end-to-end speech processing toolkit https://github.com/espnet/espnet).

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.