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Resonate

Low-latency, high-resolution spectral analysis

Details

External ID
48427423
Source
HN
Company
—
Product
Resonate
Website domain
alexandrefrancois.org
Launched
June 6, 2026
Cohort
—
Upvotes
46
Upvotes percentile
0.8346994535519126
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Last April I shared about my Resonate project here (https://news.ycombinator.com/item?id=43694157)A lot has happened since: the work I presented in much more detail at last June's International Computer Music Conference (ICMC) got best paper award. I also gave a talk at the Audio Developer Conference in Bristol last November, the video is on YouTube).This year's work, which I recently presented at this year's ICMC, starts with known techniques from the phase vocoder literature to build self-tuning filter banks that extract very efficiently the frequency components that are actually present in the input signal. Overview on the project website, more details in the papers, including applications to super-resolution spectrograms and re-synthesis experiments.As many people have pointed out, none of the techniques I have used are new (some of them even have different names across different fields), but I haven't seen them applied together in this way, and to me the results are incredibly satisfying and sometimes look magical. See for example this demo: https://youtu.be/LasdoIJJkw8Of course the best way to experience in person is through the free demo app: https://alexandrefrancois.org/OscillatorsLooking forward to feedback from the community!

Enrichment

Theme
audio and signal processing tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
Not AI
Project type
Commercial product
Normalized one-liner
spectral analysis library
Manually corrected
False

Could you build this?

No Resonate is a novel, peer-reviewed mathematical algorithm for low-latency spectral analysis using custom phasor and EWMA formulations. It represents specialized digital signal processing (DSP) academic research rather than code an LLM can simply assemble.

What it would actually take: Building Resonate requires deep theoretical understanding of discrete-time signal processing, filterbank design, and the phase vocoder. The core algorithm is implemented in C/C++ or Rust to process audio samples in real time (e.g., 44.1/48 kHz sample-by-sample update loops) with minimal latency and SIMD optimizations. Validating mathematical stability, numerical precision, and perceptual accuracy across frequency spectrums requires specialized DSP engineering skills.

Discussion

20 comments analyzed.

Competitors mentioned: MelonAid (watermelon ripeness app), Chord Detector app, Resonance Chromatic Tuner app, Siren's Chord effect

Concerns raised: Lower frequency limit (32.7 Hz) misses piano fundamentals below that threshold, iPhone microphone hardware cannot reliably capture frequencies below 50Hz, Lowest piano keys don't show lowest frequency values as expected, Poor transient handling in synthesis results, Resonator bins drift slowly and collide with each other

Feature requests: Lower frequency detection limit (down to 17Hz for watermelon ripeness detection), Better transient detection and handling, Repulsive force to prevent resonator bin collision, Adaptive timbre modeling to factor out harmonics, Frequency component tracking output as (frequency, amplitude) pairs

Competitors

Other products that read as similar to this one — 111 launches clear the similarity bar, closest 8 shown.

Attention rank: #24 of 112 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 213 days after the earliest competitor.

Other launches for this product

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