Complex Transformer: A Framework for Modeling Complex-Valued Sequence
Muqiao Yang, Martin Q. Ma, Dongyu Li, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov
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- github.com/muqiaoy/dl_signalOfficialIn paperpytorch★ 0
Abstract
While deep learning has received a surge of interest in a variety of fields in recent years, major deep learning models barely use complex numbers. However, speech, signal and audio data are naturally complex-valued after Fourier Transform, and studies have shown a potentially richer representation of complex nets. In this paper, we propose a Complex Transformer, which incorporates the transformer model as a backbone for sequence modeling; we also develop attention and encoder-decoder network operating for complex input. The model achieves state-of-the-art performance on the MusicNet dataset and an In-phase Quadrature (IQ) signal dataset.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| MusicNet | Complex Transformer | APS | 74.22 | — | Unverified |
| MusicNet | Concatenated Transformer | APS | 71.3 | — | Unverified |