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Vocal ensemble pitch estimation: STFT outperforms HCQT with lower cost

By PulseAugur Editorial · [1 sources] ·

A new research paper explores input representations for multi-pitch estimation in vocal ensembles, a task complicated by overlapping vocal ranges and fundamental frequencies. The study compares the harmonic constant-Q transform (HCQT) with a linear short-time Fourier transform (STFT), finding that STFT outperforms HCQT while being less computationally expensive. The research suggests that finer frequency resolution is not always beneficial for this task and that shorter analysis windows can be more effective for time-varying vocal pitches. AI

IMPACT This research could lead to more efficient and accurate audio processing tools for music analysis and generation.

RANK_REASON Academic paper published on arXiv detailing a novel approach to a specific signal processing problem. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Vocal ensemble pitch estimation: STFT outperforms HCQT with lower cost

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Academic paper published on arXiv detailing a novel approach to a specific signal processing problem. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Junyoung Koh, Hao-Wen Dong ·

    Revisiting Input Time-frequency Representations in Multi-pitch Estimation for Vocal Ensembles

    arXiv:2610.03656v1 Announce Type: cross Abstract: Multi-pitch estimation in vocal ensembles is challenging because singers occupy overlapping pitch ranges and often sing at closely spaced fundamental frequencies, causing their harmonics to overlap in time-frequency representation…

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