Evaluation of Attention Mechanisms on Text to Speech
- Resource Type
- Conference
- Authors
- Lin, Yi-Xing; Liang, Kai-Wen; Huang, Bing-Jhih; Wang, Jia-Ching
- Source
- 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW) Consumer Electronics-Taiwan (ICCE-TW), 2021 IEEE International Conference on. :1-2 Sep, 2021
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Transportation
Training
Conferences
Natural languages
Speech recognition
Speech synthesis
Task analysis
Convergence
- Language
- ISSN
- 2575-8284
Attention mechanisms have been widely used in sequence to sequence tasks. Among those tasks, attention-based neural text to speech synthesis with monotonic property has shown a powerful ability to generate natural speech. This paper introduces three different attention mechanisms designed to utilize the strict monotonic property and evaluates them in a multi-speaker TTS task.