pyAudioAnalysis
learnxinyminutes-docs
pyAudioAnalysis | learnxinyminutes-docs | |
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11 | 226 | |
5,673 | 11,163 | |
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5.0 | 9.5 | |
about 1 month ago | 7 days ago | |
Python | JavaScript | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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pyAudioAnalysis
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How would I compare two voice recordings of the same sentence and advise one speaker how to get closer to the second?
I actually came up with an el cheapo version of what I want to accomplish that isn't perfect but without any research can implement it and it may actually prove useful to language learners. PM me if you're interested in hearing it and critiquing it. I can share here that I'm using this guy's multiple repos though: https://github.com/tyiannak/pyAudioAnalysis
- How do I run code only when an audio file has bass
- A Python library for audio feature extraction, classification, segmentation and applications
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Phonetic search for audio files
Update: From one researcher to another. I was referred to a Python Audio AI project . Once I determine exactly which module to use I should be smooth sailing. I'll send more updates soon.
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Clustering songs with different lengths
Hey folks, I'm looking into clustering audio files with features extracted by pyAudioAnalysis. However, every feature (I'm interested in MFCC, spectral centroid and spread, and BPM) is extracted for each frame of the song (by default 0.05s, excluding BPM that relates to the whole) so tracks with different lengths produce arrays with different shapes.
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AUDIO ANALYSIS WITH LIBROSA
To learn more about pyAudioAnalysis here you go.
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Creating Audio Features with PyAudio Analysis
Humans are great at classifying noises. We can hear a chirp and surmise that it belongs to a bird, we can hear an abstract noise and classify it as as speech with a particular meaning and definition. This relationship between humans and audio classification forms the basis of speech and human communication as a whole. Translating this incredible ability to computers on the other hand can be a difficult challenge to say the least. Whilst we can naturally decompose signals, how do we teach computers to do this, and how do we show what parts of the signal matter and what parts of the signal are irrelevant or noisy? This is where PyAudio Analysis comes in. PyAudio Analysis is an open source Python project by Theodoros Giannakopoulos, a Principle researcher of multimodal machine learning at the Multimedia Analysis Group of the Computational Intelligence Lab (MagCIL). The package aims to simplify the feature extraction and classification process by providing a number of helpful tools at can sift through the signal and create relevant features. These features can then be used to train models for classification tasks.
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[P] Feature extraction for acoustic signals
This might be relevant, which has a set of feature extraction methods implemented: https://github.com/tyiannak/pyAudioAnalysis/wiki/3.-Feature-Extraction
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Hacker News top posts: Dec 11, 2021
A library for audio feature extraction, regression, classification, segmentation\ (2 comments)
- Audio feature extraction, classification, segmentation and applications
learnxinyminutes-docs
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Scripts should be written using the project main language
> Sure, maybe for some esoteric edge cases, but 5 mins on https://learnxinyminutes.com/ should get you 80% of the way there, and an afternoon looking at big projects or guidelines/examples should you another 18% of the way.
Not for C++, and even for other languages, it's not the language that's hard, it's the idioms.
Python written by experts can be well-nigh incomprehensible (you can save typing out exactly one line if you use list-comprehensions everywhere!).
Someone who knows Javascript well still needs to know all the nooks and crannies of the popular frameworks.
Java with the most popular frameworks (Spring/Boot/etc) can be impossible for a non-Java programmer to reason about (where's all this fucking magic coming from? Where is it documented? What are the other magic words I can put into comments?)
C# is turning into a C++ wannabe as far as comprehension complexity goes.
Right now, the quickest onboarding I've seen by far are Go codebases.
The knowledge tree required to contribute to a codebase can exists on a Deep axis and a Wide axis. C++ goes Deep and Wide. Go and C are the only projects I've seen that goes neither deep nor wide.
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100+ FREE Resources Every Web Developer Must Try
Learn x in y minutes: Concise tutorials to learn various programming languages and tools quickly.
- SQL for Data Scientists in 100 Queries
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New GitHub Copilot Research Finds 'Downward Pressure on Code Quality'
StackOverflow's making their own competing LLM for all this stuff.
IMO, one of the biggest problems with the way people use LLMs right now, is that they're being treated as a single oracle: to know Java, it must be trained on examples of Java.
It would be much better if their language comprehension abilities were kept separated from their knowledge (and there are development efforts in this direction), so in this example it would be trained to be able to be able to read a Java tutorial rather than by actually reading a Java tutorial, so when the overall system is asked to write something in Java, the language model within the system decides to do this by opening https://learnxinyminutes.com and combining the user query with the webpage.
I think this will help make the models more compact, which is a benefit all by itself, but it would also mean that knowledge can be updated much more easily.
Someone would have to actually do this in order to see if those benefits are worth the extra cost of having to load a potentially huge a tutorial into the context window, and likewise the extent to which a more compact training set makes the language comprehension worse.
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Ask HN: Programming Courses for Experienced Coders?
The project was created and is maintained by Adam Bard, but is open sourced with over 1.7k contributors since 2013
https://github.com/adambard/learnxinyminutes-docs
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Ask HN: How to learn to be a programmer in 20 years?
So you have studied programming for at least 5 years, what kinds of programs have you written? Apparently you have already applied your skills, since you have "created a good reputation among developers"? Why a time-frame of 20 years, why not 20 months or 20 weeks? Heck, you can learn a lot in even 20 days!
Once you have learned a few languages, libraries and frameworks then learning new stuff becomes much easier. At that point I'd recommend to check the website https://learnxinyminutes.com. Meanwhile, continue asking questions here and elsewhere :)
An other tip, if you are into computer science and algorithms stuff I recommend you try to solve problems which are posted at https://codegolf.stackexchange.com. You don't need to try solving them in less than X characters, but just to get them solved by any means necessary. And don't take too much bad influence from the posted solutions.
- Lean 4.0.0, first official lean4 release
- Learn X in Y Minutes
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how long will it take to learn JS?
If you want a brief overview, go to https://learnxinyminutes.com/ and look for Javascript. I guess it should be roughly the time it took to learn C++ or possibly less, but JS has its own quirks. Often learning a second language is difficult as the first.
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Anyone got good resources for experienced devs that don't know front end?
Very light compared to the other resources people have linked for you, but I love https://learnxinyminutes.com/
What are some alternatives?
librosa - Python library for audio and music analysis
learn-x-by-doing-y - ๐ ๏ธ Learn a technology X by doing a project - Search engine of project-based learning
pydub - Manipulate audio with a simple and easy high level interface
the-road-to-learn-react - ๐The Road to learn React: Your journey to master plain yet pragmatic React.js
SpeechRecognition - Speech recognition module for Python, supporting several engines and APIs, online and offline.
materials - Bonus materials, exercises, and example projects for our Python tutorials
pyAcoustics - A collection of python scripts for extracting and analyzing acoustics from audio files.
You-Dont-Know-JS - A book series on JavaScript. @YDKJS on twitter.
mingus - Mingus is a music package for Python
tour_of_rust - A tour of rust's language features
Watson Developer Cloud Python SDK - :snake: Client library to use the IBM Watson services in Python and available in pip as watson-developer-cloud
CppCoreGuidelines - The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++