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music-synthesizer-for-android
Jupyter Notebook2017–2024
google / music-synthesizer-for-android · Archived

music-synthesizer-for-android

Automatically exported from code.google.com/p/music-synthesizer-for-android

2Distinct people
9Mentions
0Explicit recommenders
452GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Automatically exported from code.google.com/p/music-synthesizer-for-android

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year9 dated mentions

Observed mentions: 2017-01-31 08:10:20 UTC to 2024-01-13 01:04:03 UTC.

012342017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC404
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC202
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

9 sources
This is for Cortex A8, which was the chip in the Nexus One. I wrote the original version of sound synthesis directly in ARM assembler[1]. It was very highly optimized, I remember using a cycle counting app that flagged any dependency chain that would cause the processor to stall, and ultimately utilization was in the 90%+ range. Back in those days, processors were simple enough you could do this kind of optimization by hand. By the time of Cortex A15 (Nexus 10 etc), instruction issue was out-of-order and much harder to reason about. The best current info I could find for the latency advice is [2]. Quoting, "Moving data from NEON to ARM registers is Cortex-A8 is expensive." Looking at [3] partially reveals the reason why: the NEON pipeline is entirely after the integer pipeline, so moves from integer to NEON are cheap, but the reverse dire
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ction is potentially a large pipeline stall. This is an unusual design decision that as far as I know is not true for any other CPUs. Edit: I found [4], which is a more authoritative source. [1]: https://github.com/google/music-synthesizer-for-android/blob... [2]: https://community.arm.com/support-forums/f/armds-forum/757/n... [3]: https://www.design-reuse.com/articles/11580/architecture-and... [4]: https://developer.arm.com/documentation/den0018/a/Optimizing...
In Reverse-engineering the Yamaha DX7 synthesizer's sound chip from die photos (2021)
The specific thing I've found least documented, yet most important for the distinctive percussive attacks of the DX7, is a random variation of the pitch envelope for the first few milliseconds of the note. That's almost short enough it could be done in the firmware, but I believe it might be in the hardware. It's not present in the msfa source, but might have been recovered by later Dexed authors (I haven't carefully looked at their code). If you get to the envelope hardware, you'll find it's just as clever as the exponential and sine generators. There's some info at [1], but it doesn't capture every single thing I found - there are cases where there is a slight amount of additional noise in the amplitude, I'm not sure whether intentional to give more character or an unintentional artifact. That's also missing from the msfa source. [1]: h
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ttps://github.com/google/music-synthesizer-for-android/blob... ETA: Also see https://levien.com/dx7-envelope.html for a somewhat interactive JavaScript implementation of the envelope algorithm. This accurately emulates the envelope shape and quantization of the DX7 (ie it uses the same reduced number of bits to drive its state machine), but I do not claim it is bit-perfect.
In The Yamaha DX7 synthesizer's clever exponential circuit, reverse-engineered
Shameless self-promotion. There's a high performance C++ (with neon simd acceleration) implementation at [0]. Note, this also compiles cleanly to wasm and runs in the browser (see the "webaudio" branch). This code is also the basis of the reasonably popular free "dexed" vst. Some of my analysis of the DX7 is on the associated wiki as well. Not to take anything away from the original posting, but if performance is a goal, this may be interesting. [0]: https://github.com/google/music-synthesizer-for-android
In Yamaha DX-7 synthesizer clone written in SuperCollider
An example of the linear-interpolated lookup table approach using fixed-point math is the sine generation[0] in my music synthesizer. It generates a table of 1024 entries, then lerps between those. This gives you precision beyond the least perceptible audio error, and is pretty fast. When I first wrote that code, I was targeting 32 bit ARM, with possibly very weak floating point units. These days, on the types of chips you'd see in phones (or computers in the $9-$40 range like rpi 3), the floating point calculation is _so_ fast (especially with simd) that the cost of the memory lookup starts dominating. So, the NEON implementation computes 4 sin values in a gulp, using a floating point polynomial approximation about the same precision as above[1]. [0] https://github.com/google/music-synthesizer-for-android/blob... [1] https://github.com/g
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In 16-bit math look-up tables – the unexpected power of scaled-integer math

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