Skill UI

A comprehensive guide for generating and packaging reproducible evidence for signal processing submissions to ICASSP. It details what reviewers prioritize (scoring scripts, dataset splits, logs) and outlines best practices to ensure that headline metrics are easily regenerated, thereby maximizing review credibility and post-publication impact.

This guide provides a structured framework for drafting professional rebuttals to academic conference reviews, such as ICASSP. It emphasizes the critical difference between correcting factual errors and addressing legitimate gaps. The focus must be on providing a clean rationale for the technical committee's acceptance, adopting a professional tone suitable for a single-blind review process, and anchoring all claims to the submitted material.

A comprehensive guide for transforming an accepted academic conference paper into its final, publishable "camera-ready" format for IEEE Xplore. Covers mandatory steps like PDF eXpress validation, completing the electronic copyright form, integrating reviewer feedback, confirming metadata, and preparing for both physical presentation and open-access publication.

A comprehensive guide for designing and auditing empirical experiments in signal processing, audio, and speech domains. It emphasizes matching standard metrics (e.g., WER, SI-SDR, PSNR) to specific tasks, establishing current strong baselines, and systematically sweeping operating conditions (like SNR or reverberation time) to ensure robust, reliable, and publication-ready results.

A comprehensive guide for authors submitting to major signal processing conferences like ICASSP. It details how to audit, define, and precisely position a paper's novelty by comparing it against specific literature lanes (SPS journals, conferences, and ML venues). Learn to articulate the technical delta against the nearest work in a constrained, four-page format.

A comprehensive guide for researchers submitting signal processing papers, detailing how to achieve rigorous reproducibility for conferences like ICASSP. It emphasizes that simply providing a model is insufficient; authors must pin down the 'scoring ruler,' data versions, front-end parameters, and computational seeds to ensure every reported metric can be independently verified.

A comprehensive guide detailing the ICASSP peer review pipeline, covering single-blind review mechanics, technical committee evaluation criteria, and the strategic importance of evidence, significance, and reproducibility in signal processing papers. Use this to craft submission strategies and decode decision letters.

A comprehensive audit guide for submitting papers to ICASSP conferences. This checklist covers crucial requirements such as the mandatory 4+1 page format, single-blind review rules (including author list inclusion), CMS portal submission protocols, EDICS metadata selection, and compliance with ethical standards. Use this guide before the deadline to avoid desk rejects.

A comprehensive guide for researchers submitting technical papers to conferences like ICASSP. It teaches how to manage extensive supplementary materials—including derivations, extra results, and multimedia—while ensuring the core 4-page paper remains self-contained and review-ready under single-blind review constraints. Focus on core claims, not volume.

A comprehensive guide for researchers determining the best conference or journal for their signal processing contribution. It helps users identify the core signal-processing primitive (e.g., estimator, transform, representation) to correctly route work between major venues like ICASSP, Interspeech, ICIP, or general ML conferences.

This comprehensive guide outlines the full project management lifecycle for submitting research papers to the ICASSP conference (IEEE Signal Processing Society). It details the annual timeline, critical milestones, backward planning heuristics, and best practices across various submission tracks to ensure timely and successful publication.

This guide details the rigorous process of condensing highly technical papers, especially in signal processing, into extremely constrained formats (e.g., 4-page conference submissions). It teaches structure, emphasizing the immediate presentation of the core signal-processing contribution, the mechanism, and task-matched metrics on the first page, ensuring the argument survives review by deep subfield experts.