lyra
regex-benchmark
Our great sponsors
lyra | regex-benchmark | |
---|---|---|
18 | 9 | |
3,720 | 309 | |
0.9% | - | |
0.0 | 0.0 | |
over 1 year ago | 17 days ago | |
C++ | Dockerfile | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
lyra
-
TSAC: Low Bitrate Audio Compression
Since Ballard's codec is "AI" based, can you add google's lyrav2 ( https://github.com/google/lyra ) and Facebook's/meta EnCodec ( https://github.com/facebookresearch/encodec ).
Also I don't seem to be able to access your page, so there might be error.
Finally, when doing opus comparison it's good now to denote if it is using Lace or NoLace decoder post processing filters that became available in opus 1.5 (note, this feature need to be enabled at compile time, and defying decode a new API call needs to be made to force higher complexity decoder) . See https://opus-codec.org/demo/opus-1.5/
-
Opus Databending Drumkit
I've thought about doing something similar for google's voice compression lyra https://github.com/google/lyra
-
Is it safe to say AV1 for video and OPUS for audio are best codecs respectively?
edit: It seems Lyra is opensource https://github.com/google/lyra
-
New Release of Audio Codec "Lyra" 1.3 (43% smaller and 20% faster)
1) https://github.com/google/lyra/releases/tag/v1.3.0
- Release Lyra 1.3.0 · google/lyra - performing arithmetic operations in 8-bit integers instead of 32-bit floats, the new model is 43% smaller (TFLite model size) and 20% faster
- Using AI to compress audio files for quick and easy sharing
-
Lyra V2 – a better, faster, and more versatile speech codec
Very impressive.
It'd be interesting to see what the lift would be to get encoding & decoding running in webassembly/wasm. Further, it'd be really neat to try to take something like the tflife_model_wrapper[1] and to get it backed by something like tsjs-tflite[2] perhaps even atop for example tfjs-backend-webgpu[3].
Longer run, the web-nn[4] spec should hopefully simplify/bake-in some of these libraries to the web platform, make running inference much easier. But there's still an interesting challenge & question, that I'm not sure how to tackle; how to take native code, compile it to wasm, but to have some of the implementation provided else-where.
[1] https://github.com/google/lyra/pull/89/files#diff-ed2f131a63...
[2] https://www.npmjs.com/package/@tensorflow/tfjs-tflite
[3] https://www.npmjs.com/package/@tensorflow/tfjs-backend-webgp...
[4] https://www.w3.org/TR/webnn/
-
Lyra 1.2.0 released with 5x speed improvement, higher quality speech, selectable bitrate (3.2, 6.0 and 9.2 kb/s), lower latency and Mac and Windows support
You can find an Android, Linux and macOS app here: https://github.com/google/lyra/actions/runs/3156735950
-
(Noob): Can Signal implement Lyra-Codec (developed by Google) for better audio quality?
Here's the repository: https://github.com/google/lyra and it's licensed under Apache.
- Lyra 0.0.2 ·The main improvement is the open-source release of the sparse_matmul library code, which was co-developed by Google and DeepMind. no more pre-compiled .so dynamic library binaries and no more restrictions on which toolchain to use, which opens up the door to port onto different platforms
regex-benchmark
-
Best regexp alternative for Go. Benchmarks. Plots.
Before we start comparing the aforementioned solutions, it is worth to show how bad things are with the standard regex library in Go. I found the project where the author compares the performance of standard regex engines of various languages. The point of this benchmark is to repeatedly run 3 regular expressions over a predefined text. Go came in 3rd place in this benchmark! From the end....
-
Rust vs. Go in 2023
* Let you clone a map without rehashing every key to a new seed. I generally measure at least 15x speedup from this alone, unlocking very useful design patterns like "clone a map and apply a few temporary updates for a one-off operation like validation or simulation" with no extra code complexity. Go gives you no better option than slowly rehashing the entire map.
And that's just hash maps. How about Go's regex engine being one of the slowest in the world while Rust's regex crate being one of the fastest:
https://github.com/mariomka/regex-benchmark#optimized
-
Regex for lazy developers
Languages Regex Benchmark
-
Elon is your new boss, time to refactor!
Java is still pretty bad compared to C# (not to mention Rust or Nim)
-
Lyra: Fast, in-memory, typo-tolerant, full-text search engine in TypeScript
https://github.com/mariomka/regex-benchmark
And the always interesting techempower Project, which leaves the implementation to participants of each round. https://www.techempower.com/benchmarks/#section=data-r21&tes...
Choose whatever category you wish there, js is faster in then go in almost all categories there.
Even though I said it before, I'm going to repeat myself as I expect you to ignore my previous message: the language doesn't make any implementation fast or slow. You can have a well performing search engine in go, and JS. The performance difference will most likely not be caused by the language with these two choices. And the same will apply with C/Rust. The language won't make the engine performant creating a maximally performant search engine is hard
-
i'd like you to meet regex-
Also, regex engines are not created equally, at all. One of the best writeups I've ever read is from the ripgrep blog. Burntsushi knows regex. There's also this benchmark site which illustrates how general language performance is an entirely different metric than regex performance. Don't assume those benchmarks will cover your particular use case, though--different regex engines might handle your particular situation differently.
-
Go performance from version 1.2 to 1.18
Interesting. Looking at this repo, they have
Rust -> Ruby -> Java -> Golang
https://github.com/mariomka/regex-benchmark
Though it appears the numbers are two years old or so, and only for 3 specific regexes.
-
Hajime can now get hardware information about your MC server, all from Minecraft itself!
id also be careful in claiming C++ std regex is faster than python, unless you actually have proof. there's a ton of information that in many cases its actually slower. https://github.com/mariomka/regex-benchmark. have you actually benchmarked your code? or was it just a naive assumption that because its C++ its just fast?
-
A Complete Course of the Raku programming language
It is a matter of personal preference.
I find that regular expressions and text-wrangling tasks are faster and easier in Perl than in other programming languages due to its accessible syntax and regular expression engine speed.
This article shows the regular expression syntax in several popular programming languages: https://cs.lmu.edu/~ray/notes/regex/
This GitHub repo gives some regex performance test benchmarks: https://github.com/mariomka/regex-benchmark Perl is pretty fast among the scripting languages that were benchmarked.
If you are familiar with C / C++, then learning Perl is relatively fast and easy: https://perldoc.perl.org/perlintro
What are some alternatives?
codec2 - Open source speech codec designed for communications quality speech between 700 and 3200 bit/s. The main application is low bandwidth HF/VHF digital radio.
hyperscan - High-performance regular expression matching library
ESP32_Codec2 - Codec2 library for ESP32 (Arduino)
regex - An implementation of regular expressions for Rust. This implementation uses finite automata and guarantees linear time matching on all inputs.
minisearch - Tiny and powerful JavaScript full-text search engine for browser and Node
sqlx - 🧰 The Rust SQL Toolkit. An async, pure Rust SQL crate featuring compile-time checked queries without a DSL. Supports PostgreSQL, MySQL, and SQLite.
Bazel - a fast, scalable, multi-language and extensible build system
orama - 🌌 Fast, dependency-free, full-text and vector search engine with typo tolerance, filters, facets, stemming, and more. Works with any JavaScript runtime, browser, server, service!
elasticsearch-py - Official Python client for Elasticsearch
raku-course
signal-ringrtc-node
rakudo-appimage