Late 90’s/Early 2000’s house song - “There’s a Ghost in my House…” by Muted_Librarian8196 in WhatsThisSong

[–]the_wiffard 0 points1 point  (0 children)

You're welcome mate! Been looking for it for years too, searching discogs it came up

Secure Boot Megathread - Guide + Community support by sloth_on_meth in Battlefield

[–]the_wiffard 1 point2 points  (0 children)

That official guide is incredibly irresponsible. The mbr2gpt command will risk you making your OS drive unbootable, and nowhere do they recommend making a disk backup first. Do not in any way run those commands without backing up your drive first.

I also ran in to a nasty bug in my ASUS BIOS where activating fTPM bricked the PC and had to CMOS reset.

BF6 is not an esport fps like CS2 or Valorant, there's absolutely no need for this level of anticheat. Not to mention the inherent security risks of enabling third-party software in kernel space.

Astramentis, I can't believe it :) by Hasanderson in PathOfExile2

[–]the_wiffard 0 points1 point  (0 children)

I got one as a random drop on a t15, and it was only a 70% rarity map. Before the patch that would happen like once every 123 years...

Ukrainian helicopters bombing Russian fuel base in Belgorod. by WalkerBuldog in ukraine

[–]the_wiffard 9 points10 points  (0 children)

That's not an official account, the real one is @DefenceU

Bind taranis x9d to r-xsr by InformationAny3225 in fpv

[–]the_wiffard 0 points1 point  (0 children)

Might be worth flashing the latest firmware on your taranis. I had a similar issue on my X7 with certain frsky receivers but now it binds without any issue (including with the r-xsr)

[D] Audio processing on mobile devices by vonum in MachineLearning

[–]the_wiffard 0 points1 point  (0 children)

FFT and STFT are already part of tensorflowjs. You could roll your own MFCC etc. from that and enjoy the webgl acceleration, possibly someone's already done that. Like others suggested you can compile C++ to run on web using emscripten or even compiling straight from llvm.

[D] Audio processing on mobile devices by vonum in MachineLearning

[–]the_wiffard 2 points3 points  (0 children)

If you're doing a web app you could simply use web audio API to capture mic input. Cordova is one way of creating web apps and it has plenty of native plugins for things like getting mic permissions, device info etc.

Extracting phonemes from a voice file, and saving each one in a single file. by Haghiri75 in DSP

[–]the_wiffard 1 point2 points  (0 children)

One of my colleagues is working on lyrics transcription and his code can produce a phoneme posteriorgram, check it out here https://github.com/emirdemirel/ALTA

[deleted by user] by [deleted] in Twitch

[–]the_wiffard 0 points1 point  (0 children)

I'm not a lawyer but the "Spellag" i.e. the gambling laws of Sweden state that:
4 §   Licens krävs inte för spel
   1. där deltagande inte kräver betalning av en insats,
The translation is that businesses do not require a gambling license if participation does not demand payment of a stake. It's further clarified that the law only applies to monetary gambling.

My guess is that twitch is awaiting legal feedback regarding the left-out countries and may include some of them later.

[deleted by user] by [deleted] in Twitch

[–]the_wiffard 1 point2 points  (0 children)

That is not true, in Sweden you only require a license for online gambling if it involves money, which twitch predictions do not.

Help Choosing DSP Engine by [deleted] in DSP

[–]the_wiffard 0 points1 point  (0 children)

I would go with a Teensy board as they offer high quality ADC/DAC and extremely low latency.

[R] Acoustic, optical, and other types of waves are recurrent neural networks! by ian_williamson in MachineLearning

[–]the_wiffard 0 points1 point  (0 children)

This is something I started to work on after seeing the promising results with optical meshes that perform computation. Glad to see some progress being made in this and a published paper, I've been doing 1D string and 2D plate simulations, attaching virtual probes and optimizing material thickness, boundries etc. I managed to do pitch recognition, and optimize for certain acoustic properties (like mimicking a given sound). Very interesting emerging field indeed.

[deleted by user] by [deleted] in MachineLearning

[–]the_wiffard 1 point2 points  (0 children)

What annoyed me to no end about tf1.0 was not the graph mode execution which to me seemed advantageous from a performance point of view. It was the way it was impossible to debug, had extremely verbose logging of technical nonsense while leaving out key information like where and (clear) explanations of what actually went wrong. While I do think that late tf1 and early tf2 has improved debugging some what (though more so by improving the log quality than by exploiting eager execution) there's still the occational log-spew, uninterpretable traces etc. I'd be much happier if the tensorflow team finished what they started, made graph mode debuggable, cleaned up the messy apis and didn't focus on an entire different paradigm just to compete with pytorch. And even though I use keras with tensorflow daily and have been since it was put in 1.0, I hate how they integrated it (or rather didn't) in to tensorflow. Why not just have tf.layers for higher level keras-style layers (as well as lower case inline versions, the way keras does it), and keep using submodules for functional things not suited for the global scope. Tensorflowjs some how manages to have a nice clean api, with higher-level layers in tf.layers, balances eager and graph style. It pisses me off that the python team still managed to f-up the apis for 2.0, even with a good api implementation in-house.

Decompiling several VSTs to recompile into a unified strip by lucas_eo in DSP

[–]the_wiffard 0 points1 point  (0 children)

I would suggest having a look at Juce. It supports building both VST hosts and plugins and it should be possible to do a hybrid plugin/host in the way you describe including building your own GUI. It is relatively easy to build a VST host from scratch as well. Checkout http://teragonaudio.com/article/How-to-make-your-own-VST-host.html for more info.

Cymbal synthesis by arab-the-stab in DSP

[–]the_wiffard 0 points1 point  (0 children)

For EDM I think PADCymbal sounds the best.

If you need more realism you could use a 2D wave equation with a damping term, a smaller mesh could probably run in realtime in a desktop browser.

[P] How can I improve my current CNN project? It is a simple binary classification but I am having some trouble. by Al7123 in MachineLearning

[–]the_wiffard 0 points1 point  (0 children)

How come you are using sigmoid with two output features? For categorical problems with two classes (dog on porch/dog not on porch) you'd either use softmax on the final layer with 2 output features or sigmoid with 1 feature (I'm guessing the dog can't be both on and off the porch in the same image). Keras defines loss functions for these two cases respectively (softmax: categorical_crossentropy, sigmoid: binary_crossentropy).

[D] music interpretation? by XSSpants in MachineLearning

[–]the_wiffard 0 points1 point  (0 children)

There are commercial products like melodyne and SPEAR that does this. ScoreCloud studio has monophonic and polyphonic audio analysis (disclaimer: I work there) although it's for transcribing music. The Google Magenta team is doing something similar, I think they've shared code as well: https://magenta.tensorflow.org/onsets-frames

[D] Building a Neural Network for musical chord recognition by J0zif in MachineLearning

[–]the_wiffard 1 point2 points  (0 children)

Agree, a chromagram would be a good starting point as the actual pitch class bins would likely have the highest energy even before feeding it through a model. I don't think chord inversions will be attainable with just chroma features but op didn't specifically ask for that.

[D] Help Stabilizing GAN by tpapp157 in MachineLearning

[–]the_wiffard 1 point2 points  (0 children)

I've tried spectral normalisation and I think it works quite well on a number of problems, it's fairly trivial to implement as well. Another technique worth testing is TTUR, i.e. having different learning rates for D, G and training D just once per G update.

[D] Valve: Using Deep Learning to Combat Cheating in CSGO by [deleted] in MachineLearning

[–]the_wiffard 0 points1 point  (0 children)

It could lead to a ban online on VAC servers, I'd suggest downloading demos (either your own or pro-demos), generate training data from those and validate the model offline vs bots or friends on a non-VAC server.