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We've released an open-source implementation of STIPA (Speech Transmission Index for Public Address) on GitHub!
GitHub Repository: https://github.com/zawi01/stipa
What is STIPA?
Speech Transmission Index is a metric designed to assess the quality of speech transmission through a communication channel. It quantifies the intelligibility of speech signals based on amplitude modulations, providing a standardized measure crucial for evaluating public address systems and communication equipment. STIPA is a version of STI using a simplified measurement method and only one test signal.
Quality Representation:
STI values range from 0 to 1, categorizing speech transmission quality from bad to excellent. The raw STI score can be transformed into the likelihood of intelligibility of syllables, words, and sentences being comprehended.
Verification Tests:
To ensure reliability, we've conducted verification tests according to the IEC 60286-16 standard. Download the test signals and run the stipaVerificationTests.m script from our GitHub repository.
Control Measurements:
We've performed comparative measurements in a university auditorium, showcasing the validity of our implementation.
License:
Our STIPA implementation is distributed under the GNU General Public License 3, reflecting our commitment to open-source collaboration.
I have been finding the AI Chat Playground very useful for daily MATLAB use. In particular it has been very useful for me in basically replacing or supplementing dives into MATLAB documentation. The documentation for MATLAB is in my experience uniformly excellent and thorough but it is sometimes lengthy and hard to parse and the AI Chat is a great one stop shop for many questions I have. However, I would find it very useful if the AI Chat could answer my queries and then also supply a link directly to the documentation. E.g. a box at the bottom of the answer that is basically
"Here is the documentation on the functions AI Chat referred to in this response"
could be neat.
I recently wrote about the new ODE solution framework in MATLAB over the The MATLAB Blog The new solution framework for Ordinary Differential Equations (ODEs) in MATLAB R2023b » The MATLAB Blog - MATLAB & Simulink (mathworks.com)
This was a very popular post at the time - many thousands of views. Clearly everyone cares about ODEs in MATLAB.
This made me wonder. If you could wave a magic wand, what ODE functionality would you have next and why?
Over at Reddit, a MATLAB user asked about when to use a script vs. a live script. How would you answer this?
Hi
I am using simulink for the frequency response analysis of the three phase induction motor stator winding.
The problem is that i can't optimise the pramaeter values manually, for this i have to use genetic algrothem. But iam stucked how to use genetic algorithum to optimise my circuit paramter values like RLC. Any guidence will be highly appreciated.
Starting with MATLAB can be daunting, but the right resources make all the difference. In my experience, the combination of MATLAB Onramp and Cody offers an engaging start.
MATLAB Onramp introduces you to MATLAB's basic features and workflows. Then practice your coding skill on Cody. Challenge yourself to solve 1 basic problem every day for a month! This consistent practice can significantly enhance your proficiency.
What other resources have helped you on your MATLAB journey? Share your recommendations and let's create a comprehensive learning path for beginners!
AMIT SURYAVANSHI
AMIT SURYAVANSHI
Last activity am 13 Jan. 2024

Software defined ration

i am just thinking to make a project on software defined ratio SDR using matlab and its toolboxes but I am UG student in ECE don't know how to start can we have discussion here and want the guidance from the best or good persons in the field of wireless communication
I am a beginner of deep learning, and meet with some problems in learning the MATLAB example "Denoise Signals with Adversarial Learning Denoiser Model", hope very much to get help!
Denoise Signals with Adversarial Learning Denoiser Model - MATLAB & Simulink - MathWorks China
1. visualizaition of the features
It is my understanding that the encoded representation of the autoencoder is the features of the original signal. However in this example, the output dimension of the encoder is 64xSignalLength. Does it mean that every sample point of the signal has 64 features?
2. usage of the residual blocks
The encoder-decoder model uses residual blocks (which contribute to reconstructing the denoised signal from the latent space, ). However, only the encoder output is connected to the discriminator. Doesn't it cause the prolem that most features will be learned by the residual blocks, and only a few features that could confuse the discriminator will be learned by the encoder and sent to the discriminator?
I would tell myself to understand vectorization. MATLAB is designed for operating on whole arrays and matrices at once. This is often more efficient than using loops.
Matt J
Matt J
Last activity am 29 Jan. 2024

3D polyshapes

Is there a reason for TMW not to invest in 3D polyshapes? Is the mathematical complexity of having all the same operations in 3D (union, intersection, subtract,...) prohibitive?
James Prestegard
James Prestegard
Last activity am 12 Jan. 2024

Training a deep neural net

I have been developing a neural net to extract a set of generative parameters from an image of a 2-D NMR spectrum. I use a pair of convolution layers each followed by a fullyconnected layer; the pair are joined by an addtion layer and that fed to a regression layer. This trains fine, but answers are sub-optimal. I woudl like to add a fully connected layer between the addtion layer and regression, but training using default training scripts simply won't converge. Any suggestions? Maybe I can start with the pre-trained weights for the convolution layers, but I don't know how to do this.
JHP
I noticed a couple new replies show up on the recent poll a day or so ago, but since then, the page can't be loaded anymore in any browser I've tried.
https://www.mathworks.com/matlabcentral/discussions/highlights/838494
cui,xingxing
cui,xingxing
Last activity am 4 Jan. 2024

Matlab full support for python?

Is MathWorks going to spend 5 years starting in 2024 making Python the #1 supported language?
https://programmerhumor.io/programming-memes/the-pain-and-suffering-caused-by-matlab-will-finally-end-soon/
I'm not sure it's authentic information, and am looking forward to a high level of integration with python.
Reference:
https://www.mathworks.com/content/dam/mathworks/fact-sheet/using-matlab-with-python-cheat-sheet.pdf?source=15572&s_eid=psm_15572
Shore
Shore
Last activity am 30 Dez. 2023

AI Chat: Thumbs Up/Down

This is not a question, it is my attempt at complying with the request for thumbs up/down voting. I vote thumbs up, for having AI.....
I am not sure if specific AI errors are to be reported. Other messages I just read from others here and the AI Chat itself clearly state that errors abound.
My AI request was: "Plot 300 points of field 2"
AI Chat gave me, in part:
data = thingSpeakRead(channelID, 'Fields', 2, 'NumPoints', 300, 'ReadKey', readAPIKey);
% Extract the field values
field1Values = data.Field1;
% Plot the data
plot(field1Values);
The AI code failed due to "Dot indexing is not supported for variables of this type"
So, I corrected the code thus to get the correct plot:
data = thingSpeakRead(channelID, 'Fields', 2, 'NumPoints', 300, 'ReadKey', readAPIKey);
% Extract the field values
%field1Values = data.Field1;
% Plot the data
plot(data);
I see great promise in AI Chat.
Opie
Explore all the capabilities for Modeling Dynamic Systems while keeping them handy with this Cheat Sheet - Download Now.
Quick answer: Add set(hS,'Color',[0 0.4470 0.7410]) to code line 329 (R2023b).
Explanation: Function corrplot uses functions plotmatrix and lsline. In lsline get(hh(k),'Color') is called in for cycle for each line and scatter object in axes. Inside the corrplot it is also called for all axes, which is slow. However, when you first set the color to any given value, internal optimization makes it much faster. I chose [0 0.4470 0.7410], because it is a default color for plotmatrix and corrplot and this setting doesn't change a behavior of corrplot.
Suggestion for a better solution: Add the line of code set(hS,'Color',[0 0.4470 0.7410]) to the function plotmatrix. This will make not only corrplot faster, but also any other possible combinations of plotmatrix and get functions called like this:
h = plotmatrix(A);
% set(h,'Color',[0 0.4470 0.7410])
for k = 1:length(h(:))
get(h(k),'Color');
end
We are thrilled to announce the grand prize winners of our MATLAB Flipbook contest! This year, we invited the MATLAB Graphics Infrastructure team, renowned for their expertise in exporting and animation workflows, to be our judges. After careful consideration, they have selected the top three winners:
1st place - Rolling fog / Tim
Judge comments: Creative and realistic rendering with well-written code
2nd place - Christmas Tree / Zhaoxu Liu
Judge comments: Festive and advanced animation that is appropriate to the current holiday season.
3rd place - Energy / Nikolay Velkov
Judge comments: Nice translation of existing shader logic to MATLAB that produces an advanced and appealing visual effect.
In addition, after validating the votes, we are pleased to announce the top 10 participants on the leaderboard:
Congratulations to all! Your creativity and skills have inspired many of us to explore and learn new skills, and make this contest a big success!
The MATLAB Flipbook Mini Hack contest has concluded! During the 4 weeks, over 600 creative animations have been created. We had a lot of fun and a great learning experience! Thank you, everyone!
Now it’s the time to announce week 4 winners. Note that grand prize winners will be announced shortly after we validate votes on winning entries.
Realism:
Tim / Moonrun
Daniel Pereira / Earth with labels!
O / Skywheel
Vasilis Bellos / Isle of Storms
Holiday & Season:
Zhaoxu Liu / slandarer / The Fierce Ghost of Halloween
Shanshan / Snowman
Jr / timeless 80s
Abstract:
VMM / Diffusion/Reaction
Adrien Leygue / a walk in 13D
Jan Studnicka / River
Nikolay Velkov / Energy
leon t / Stable Manifold of Lorenz System
Cartoon:
Sarah / rock hammer
Congratulations, weekly winners!We will reach out to you shortly for your prizes.
Looking for an opportunity to practice your AI skills on a real-world problem? Interested in AI for climage change? Sign up for the Kelp Wanted challenge, which tasks participants with developing an algorithm that can detect the presence of kelp forests from satellite images.
Participants of all skill levels from anywhere in the world are welcome to compete!
MathWorks provides the following resources for all participants: