STFTCodec: High-Fidelity Audio Compression through Time-Frequency Domain Representation
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Abstract (arXiv)
We present STFTCodec, a novel spectral-based neural audio codec that efficiently compresses audio using Short-Time Fourier Transform (STFT). Unlike waveform-based approaches that require large model capacity and substantial memory consumption, this method leverages STFT for compact spectral representation and introduces unwrapped phase derivatives as auxiliary features. Our architecture employs parallel magnitude and phase processing branches enhanced by advanced feature extraction mechanisms. By relaxing strict phase reconstruction constraints while maintaining phase-aware processing, we achieve superior perceptual quality. Experimental results demonstrate that STFTCodec outperforms both waveform-based and spectral-based approaches across multiple bitrates, while offering unique flexibility in compression ratio adjustment through STFT parameter modification without architectural changes.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Mar 2025.
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Citing papers per year: 2026: 4.
4 papers.
- 2026Listen, Look, Drive: Coupling Audio Instructions for User-aware VLA-based Autonomous Drivingcited by 2
- 2026EuleroDec: A Complex-Valued RVQ-VAE for Efficient and Robust Audio Codingcited by 1
- 2026Modeling Music as a Time-Frequency Image: A 2D Tokenizer for Music Generationcited by 1
- 2026E^2-LLM: Bridging Neural Signals and Interpretable Affective Analysiscited by 0
- 2026Modeling Music as a Time-Frequency Image: A 2D Tokenizer for Music Generation15 May 2026
- 2026EuleroDec: A Complex-Valued RVQ-VAE for Efficient and Robust Audio Coding24 Jan 2026
- 2026Listen, Look, Drive: Coupling Audio Instructions for User-aware VLA-based Autonomous Driving17 Jan 2026
- 2026E^2-LLM: Bridging Neural Signals and Interpretable Affective Analysis11 Jan 2026