Signals 4 · free daily AI digest

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

Paper recorded by Signals 4 on 2026-10-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05

Category: cs.AI · 人工智能 · first seen 2026-10-05

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 representations. Existing models commonly use harmonic constant-Q transform (HCQT)-based representations to provide frequency-adaptive resolution, at the cost of expensive feature extr

Read on arXiv →

#467 most recent of 980 cs.AI papers we have recorded · ↑ newer: FrugalEvo: Towards Cost-Aware LLM-Guided Program Evolution · ↓ older: MRVQ: One Resident Index for Dimension- and Rate-Elastic Vector Search
Cite this page: Revisiting Input Time-frequency Representations in Multi-pitch Estimation for Vocal Ensembles: the #467 most recent of 980 cs.AI papers we have recorded (as of 2026-10-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/revisiting-input-time-frequency-representations-in-multi-pitch-estimation-for-vo.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions