CMLab

5 ms·

1.
by CMLab 2y ago
AI cover song platforms, How to address issues related to copyright, legal, and ethical concerns?
2.
Show HN: Free Tools for Tabs, Chords, Lyrics Use 8 A100 GPUs(lamucal.com)
30 points by CMLab 2y ago|5 comments
3.
CoverNet – A transformer-based model for voice timbre clone(github.com)
1 points by CMLab 2y ago|0 comments
4.
by CMLab 2y ago
When github release?
5.
AudioFlux: A C/C++ library for audio and music analysis(github.com)
230 points by CMLab 2y ago|54 comments
6.
A transformer-based model with 1 min data for voice retrieval(github.com)
1 points by CMLab 2y ago|0 comments
7.
Lamucal.ai: Vocal Remover, Real-Time chords and lyrics for music(lamucal.ai)
3 points by CMLab 2y ago|0 comments
8.
by CMLab 2y ago
At this point, I'm conflicted. The lyrics testing went well for me, but I'm not proficient in chords. Are the chord results really that poor? I wonder if I can use it to play my favorite songs in real life.
9.
by CMLab 2y ago
I tried a few songs and uploaded one of my favorite songs. The lyrics recognition result was excellent, but there were a few instances where some words were missing or incorrect. It would be great if there could be an option to edit the lyr
10.
by CMLab 2y ago
Data sourced from YouTube, which may be helpful for singing or playing the guitar.
11.
MuiscNN: A transformer-based multimodal model for music(github.com)
4 points by CMLab 2y ago|1 comments
12.
by CMLab 2y ago
Get chords, beats, lyrics, melody, and tabs for any song.
13.
Lamucal – An AI-powered multimodal project focused on music(github.com)
3 points by CMLab 2y ago|1 comments
14.
by CMLab 3y ago
Based on our current tests, our algorithm shows significantly higher accuracy and robustness compared to traditional digital signal algorithms such as PEF, NCF, YIN, HPS, etc. Our team is working diligently, and we will release benchmark te
15.
by CMLab 3y ago
Thank you for providing error feedback. We will work hard to address it. Currently, the model-related data is relatively large, which may be related to network speed.
16.
by CMLab 3y ago
CREPE generally has high latency and error rates in instrument pitch recognition, especially for guitar instruments. Our team will release benchmark test data and results later.
17.
TuneNN: A transformer-based network model for pitch detection(github.com)
112 points by CMLab 3y ago|39 comments
18.
by CMLab 3y ago
A transformer-based network model, pitch tracking for musical instruments. The timbre of musical notes is the result of various combinations and transformations of harmonic relationships, harmonic strengths and weaknesses, instrument resona
19.
by CMLab 3y ago
It supports dozens of time-frequency analysis transformation methods and hundreds of corresponding time-domain and frequency-domain feature combinations, can be provided to deep learning networks for training.
20.
by CMLab 3y ago
Cool, I want to make a guitar tuner on the mobile end. I don't know if it supports it?
21.
JsonParse: A Simple JSON parser in ANSI C(github.com)
3 points by CMLab 4y ago|1 comments
22.
by CMLab 4y ago
jsonParse is simple ,only 1600+ lines code
23.
Van: A functional-programming and object-oriented-programming script language(github.com)
5 points by CMLab 4y ago|2 comments
24.
by CMLab 4y ago
Van is a script language, implement in ANSI C.
25.
by CMLab 4y ago
The synchrosqueezing or reassignment is a technique for sharpening a time-frequency representation
26.
by CMLab 4y ago
It is worth discussing whether the domain specific language design for ChartML is necessary for users.
27.
by CMLab 4y ago
I am interested deep learning for audio, develop open source projects with some like-minded friends: https://github.com/libAudioFlux/audioFlux
28.
by CMLab 4y ago
Thanks for publishing. Is it open source？
29.
AudioFlux: a deep learing tool for audio feature extraction(audioflux.top)
1 points by CMLab 4y ago|1 comments
30.
by CMLab 4y ago
A library for audio and music analysis and feature extraction, which supports dozens of time-frequency analysis and transformation methods, as well as hundreds of corresponding time-domain and frequency-domain feature combinations, can be p

More ›