DOSE : Drum One-Shot Extraction from Music Mixture

Drum one-shot samples are crucial for music production, particularly in sound design and electronic music. This paper introduces Drum One-Shot Extraction, a task in which the goal is to extract drum one-shots that are present in the music mixture. To facilitate this, we propose the Random Mixture One-shot Dataset (RMOD), comprising large-scale, randomly arranged music mixtures paired with corresponding drum one-shot samples. Our proposed model, Drum One- Shot Extractor (DOSE), leverages neural audio codec language models for end-to-end extraction, bypassing traditional source separation steps. Additionally, we introduce a novel onset loss, designed to encourage accurate prediction of the initial transient of drum one-shots, which is essential for capturing timbral characteristics. We compare this approach against a source separation-based extraction method as a baseline. The results, evaluated using Frechet Audio Distance (FAD) and Multi-Scale Spectral loss (MSS), demonstrate that DOSE, enhanced with onset loss, outperforms the baseline, providing more accurate and higher-quality drum one-shots from music mixtures. The code, model checkpoint, and audio examples are available at https://github.com/HSUNEH/DOSE

Sub-Nyquist Sampling OFDM Radar With a Time-Frequency Phase-Coded Waveform

This paper presents a time-frequency phase-coded sub-Nyquist sampling orthogonal frequency division multiplexing (PC-SNS-OFDM) radar system to reduce the analog-to-digital converter (ADC) sampling rate without any additional hardware or signal processing. The proposed radar divides the transmitted OFDM signal into multiple sub-bands along the frequency axis and provides orthogonality to these sub-bands by multiplying phase codes in both the time and frequency domains. Although the sampling rate is reduced by the factor of the number of sub-bands, the sub-bands above the sampling rate are folded into the lowest one due to aliasing. In the process of restoring the signals in folded sub-bands to those in full signal bands, the proposed PC-SNS-OFDM radar effectively eliminates symbol-mismatch noise while introducing trade-offs in the range and Doppler ambiguities. The utilization of phase codes in both the frequency and time domains provides flexible control of the range and Doppler ambiguities. It also improves the signal-to-noise ratio (SNR) of detected targets compared to an earlier sub-Nyquist sampling OFDM radar system. This is validated with simulations and experiments under various sub-Nyquist sampling rates.