Enhancing Local Dependencies for Transformer-Based Text-to-Speech via Hybrid Lightweight Convolution
Owing to the powerful self-attention mechanism, the Transformer network has achieved considerable successes across many sequence modeling tasks and has become one of the most popular methods in text-to-speech (TTS). The vanilla self-attention excels in capturing long-range dependencies but suffers i...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9376936/ |