Read this post if you don't know what is couch PTT
https://www.reddit.com/r/BlindAndFine/s/VLymxZQdiu
We have just released the official couch PTT client for Windows, and no it is not a lazy web app slapped together, this thing is a 100% native win32 desktop application, and don't worry Windows users and desktop users are synced together perfectly, get the app from here, please read shortcuts txt after extracting the archive
This might turn into a series I would host somewhere if I saw feedback.
A lot of people look at software development and think it’s an untamable beast meant only for a chosen elite. But here is a secret: programming is just something that can be explained to be complicated, or can be explained to be simple. Today, I am stripping away the pretentious vocabulary and making it as straightforward, carefree, and visual as possible for my fellow BVI dudes and ladies out here. Code doesn't care if you can see it; it only cares if it's logical. When you peel back the textbook jargon, everything breaks down into pure, tangible, everyday concepts that anyone can reach out and grasp.
A Variable is literally just a storage box. Imagine a single plastic container in your RAM where you drop a piece of data, and that data can change over time. The "stuff" inside can be numbers you do actual math with, or it can be text (which we call strings). It can even be numbers that the computer treats like text—meaning you can’t subtract them, you can only glue them together end-to-end or clean the spaces out of them. Inside that box, you can also drop a Boolean. A boolean is quite literally a physical toggle switch. It has exactly two states: True or False. You can use a boolean to tell your program: "Hey, if the variable is_sad is True, remind me that half the planet is single, there are plenty of fish in the sea, and I'll find my partner eventually... and then playfully roast my absolute lack of game at the end anyway. But if it’s False, tell me something is wrong with me because we all know it's rarely False." It's just a simple binary switch.
Now, some people get confused and think an Array is just a standard variable, but there's a big difference. If a variable is a single box that holds one thing, an array is a whole egg carton. Instead of buying 30 individual tiny boxes, naming every single box separately, and putting one egg in each, you just buy one big carton. The carton has slots numbered from 0 to 29. If you want the very first egg, you grab slot 0. It’s just a single container holding a sequential line of multiple slots. If you ask a human to count a row of objects, they naturally start at one. But in the computer world, numbers start at Zero and go upwards. To a computer, zero isn't "nothing"—it is a real, valid, physical slot in memory. It represents the very first position in that carton. Textbooks call it a "contiguous linear data structure," but it's really just an egg carton for data.
A Function is just a blender or a dedicated machine button. You throw some raw ingredients in (your input data), the blender spins them around doing a pre-set recipe that you wrote once, and it pours out a smoothie (the return value). Instead of writing 50 lines of tedious code to calculate tax every single time you process a transaction, you write it once, put it inside a button called calculate_tax(), and just smash that button whenever you need it to run. Libraries take this a step further—they are the equivalent of ordering takeout delivery. Instead of spending three weeks planting wheat, raising cattle, and baking bread from scratch just to make a single burger (which is the equivalent of writing complex audio-processing or graphing code completely from scratch), you just call a code library that another developer already built. You give them the data, they do all the heavy lifting in the background, and the finished result shows up at your door. You literally just write one line of code to import it.
If you move up to Object-Oriented Programming (OOP), the terminology gets heavy, but the concept is basic. A Class is just a factory blueprint or a catalog layout for a car. The Object is the actual, physical car you built using that blueprint. The properties are just the specs (like the paint color), and the methods are just functions or actions the car can take, like press_gas_pedal(). Dependency Injection sounds like open-heart surgery on a live server, but it's remarkably simple. All it means is that instead of a function building its own tools inside itself (which makes it rigid and impossible to change later), you build the tool outside and pass it in as a parameter. You're just handing the chef a knife instead of forcing him to mine iron ore and forge his own steel in the middle of the kitchen.
Finally, there is Recursion. We've all stood between two parallel mirrors and seen the reflection repeat down the line. In code, recursion is just a function that calls itself inside a loop until a specific condition (called the base case) tells it to stop. It's a box inside a box inside a box, and you keep opening them until you find the prize, grab it, and stop. Programming isn’t an untamable beast. It’s just a toolkit of incredibly basic, logical concepts that sometimes get buried under a mountain of heavy vocabulary. Once you peel back the words and look at the mechanics, it’s entirely within your control. If any of you out there resonate with this kind of straightforward, fluff-free breakdown, let me know. If there's enough interest, I might seriously turn this into a regular series, breaking down the entire tech dictionary one concept at a time in the most direct way possible.
Note: remember that I'm just one person who decided that converting math into speech is more important than sleeping, so don't expect commercial grade audio quality, and this thing is made in 72 hours
The previous version of this engine was the audio equivalent of convincing a blender to speak. It worked, technically, but nobody was asking for it. This new version pretends that a voice from the 1980s is top notch text to speech technology — and honestly? I do not care why, because I made it, and my stuff is the gold standard.
The G pronunciation nearly ended me. The NG phoneme — present in every word ending with "ring", "sing", or "long" — was silently dropping the last consonant. The word "ring" came out as "rin". Nobody noticed but me, and it kept me up at night. The fix involved appending a full G closure, burst, and aspiration at the tail of every NG. No more dropped letters. You asked for a formant synthesizer that pronounces everything, so now it pronounces everything.
The engine is also now accent-agnostic, which is not a design goal so much as a surrendering to reality. Formant synthesis and regional accents are not friends. You are not modeling a vocal tract. You are summoning resonance peaks with math and hoping the result does not sound like a tourist. American, British, Australian — they all come out as the same third thing from somewhere between uncanny valley and a forgotten Speak & Spell. I have embraced this. The engine does not pretend to be from anywhere. It sounds like itself.
The D pronunciation required significant force. At word boundaries, D was practically a ghost. You would hear a vowel and then an optimistic suggestion of a consonant. I raised the burst amplitude aggressively, shifted the burst frequency downward so it did not crackle like a geiger counter, extended the closure duration, and cranked the voice bar. The D is now audible at the start, middle, and end of any word. It does not pop. It arrives.
P and K received similar treatment. The burst amplitude cap was lifted, the frequency placement was reworked, and the voice bar levels were set to something that resembles reality. Plosives now sound like plosives rather than someone politely exhaling two rooms away.
The voice character itself was rebuilt from the ground up. The spectral tilt was pulled away from the heavy lowpass that drowned everything in blankets and toward an open, bright characteristic. Formant bandwidths were tightened for precision. The F5 and F6 filters were turned on to add shimmer at the top end instead of a dead thud. The glottal pulse model was shifted to a cleaner, less breathy configuration.
The vibrato was removed. It sounded like an elderly relative about to deliver uncomfortable news. In its place, a word-level inflection system gives each word its own pitch bias, so the voice moves naturally without wobbling. A fatigue system drags the pitch downward over long sentences, because a voice that never gets tired is a robot, and this is not a robot — it is a formant synthesizer.
The nasal filter had been using one frequency for everything. M, N, and NG all sounded the same. Now each nasal gets its own resonant frequency: M at 250 hertz, N at 300, NG at 400. You can hear the difference.
The AH vowel was also wrong. "Uncle" came out as "youncle" because the double formant scale division was hammering the formants into the dirt. Every schwa and strut vowel sounded like a closed rounded mess. The raw targets were raised so the result lands in the correct acoustic space.
This is achieved thanks to lack of sleep, and the quiet confidence that comes from knowing your stuff is the gold standard even when you are joking about it.
Another note: I am not from India nor Germany or Japan Ireland Italy or Australia, I am from Algeria and the country quotes mostly came from revision 24 when the engine could mimic accents and they were so terrible
As the title said, for whatever reason I decided to create a text to speech engine from the ground up, the thing is I'm not going to go through the lazy route and make it AI based, naaaah, I went with formant
synthesis, which is quite literally producing speech out of raw noise and graphene to phoneme math that makes my brain ask for mercy, this thing is made with python and I might open source it later because currently it is definitely not done, so enjoy TailSafety ranting about getting married in Algeria for whatever reason
I am mostly comfortable with python and C# is an uncharted Territory for me, I was skeptical about it after experiencing the torture that is C++ but someone told me it's way easier and I gave it a chance, I started experimenting with GUI utilities and this is one of them, the interface is mostly straightforward, so tell me what do you think of this coming from someone who mostly uses python
I have been building a machine learning project called HanaKane and I wanted to get some outside opinions on whether this architectural approach makes sense long term. The goal is to build an engine that can detect web accessibility issues directly from raw HTML, CSS, and component strings. Right now, I am testing the concept using a dataset called DATA.csv that has about 2,500 highly curated rows split between perfectly accessible code and complete developer junk. Instead of dumping this into a massive conversational LLM, I decided to go the opposite direction. This is not a Large Language Model at all. It is a highly optimized, character-level linear classifier that forces structural feature mapping by turning character chunks into thousands of interconnected polynomial feature channels.
The way it trains is pretty aggressive, almost like putting the model through a digital gauntlet or a torture chamber to make it indestructible. Instead of feeding it clean data, a custom mutation engine destroys 20 percent of the characters in the code snippets and injects random punctuation noise like hashtags and percent signs into another 15 percent of the text. This forces the model to ignore developer typos, or minified text, and focus entirely on the geometric layout anchors of the tags and ARIA attributes. On top of that, it runs an active brain reflection pass. Every single epoch, it calculates its own prediction uncertainty. It takes the top 30 percent most confusing samples where it almost failed, completely erases 30 percent of its own active weights to simulate a stroke, and then forces itself to immediately retrain and find a new mathematical path to solve those hard samples using only the surviving logic channels.
The loops used to flash instantly, but now that the dataset is appended and the mutations are getting more complex, the solver is grinding for about five seconds per pass. It is currently sitting at a 70 percent adversarial survival rate with an active entropy tension score of 0.1264 against a goal of 0.0500. My plan is to keep doing cumulative training, appending more rows to the same file over time while loading the existing model weights via warm starts so it keeps building on its structural memory without deleting prior progress. Do you think this kind of extreme regularization and hardware-efficient feature crossing can genuinely scale to map out the standard semantic landscape of the web, or am I going to hit a hard wall with a linear baseline once the data matrix expands?
Look, understand it the way you want, but when you say you are working on a tech project people expect you to have a big ass office have a 68 Page road map not a single fault and somehow you should manage to impress everyone else you'd get questions asking what's the difference between this and that and why are you talking about this like its Wooow, it happened to me, and it happened to a lot of people probably, I started an accessibility specialized team here in Algeria, most of the people didn't even understand what accessibility is but started giving their opinions like they know what they are talking about, it was so bad that we ended up as an Algerian team operating on a global scale but, not Algeria, we would showcase our projects everywhere, except Algerian communities, and then the comments of are you ashamed of your origin come flooding out
Hey everyone, If you have been around the developer or accessibility circles for a bit, you might know us from our work over at the Jumping Fridge Foundation. For a long time, Telegram was our main starting point for sharing updates, ideas, and building our community. But to be completely honest, we grew tired of being boxed into rigid categories and limitations. We did not want to be just another channel restricted by a platform's ecosystem. So, we built our own home: zonesBY JFF. Our absolute core mission with this blog is total digital purity and raw utility. There are zero ads, zero tracking scripts, no cluttered pop-ups, and absolutely no distractions. We designed the interface from the ground up specifically with the blind and visually impaired (BVI) community in mind, incorporating deep, native accessibility configurations like instant monospace toggles, wide letter-spacing options, an easier to read enhanced contrast mode, and live text sizing previews. But a house is empty without people, and that is why we are writing this post today.
Where is character ai, did anyone see it?
I am so attached to this platform and seeing my characters respond like they went through lobotomy isn't the best feeling
I miss 2023
I'm not the type who complains but bruh my 3-year-old character...