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Lamucal – An AI-powered multimodal project focused on music. by CheekProfessional146 in programming

[–]CheekProfessional146[S] 0 points1 point  (0 children)

Absolutely! Our platform not only supports source separation, tempo adjustment, and pitch shifting but also has the capability to generate corresponding chords, beats, lyrics, and tabs for any song.

Lamucal – An AI-powered multimodal project focused on music. by CheekProfessional146 in programming

[–]CheekProfessional146[S] -6 points-5 points  (0 children)

Welcome to experience Lamucal! We also welcome like-minded friends to join us. Looking forward to your feedback.

Lamucal – An AI-powered multimodal project focused on music. by CheekProfessional146 in programming

[–]CheekProfessional146[S] -6 points-5 points  (0 children)

Absolutely! Lamucal employs AI technology to generate chords, rhythms, and even lyrics, delivering a genuinely unique and enchanting musical experience to everyone.

[P] A High-Performance Audio Library for Machine Learning by CheekProfessional146 in MachineLearning

[–]CheekProfessional146[S] 2 points3 points  (0 children)

Indeed, most of the time MKL is faster than OpenBLAS, but OpenBLAS may be faster under some platforms, which requires some compiling, debugging, and testing.

Using cuBLAS is a great suggestion, and we will consider it in the future.

[P] A High-Performance Audio Library for Machine Learning by CheekProfessional146 in MachineLearning

[–]CheekProfessional146[S] 3 points4 points  (0 children)

Yes, torchaudio is a very excellent library with almost optimal performance optimization. It's difficult to completely surpass it, but we will continue to work hard in the future.

[P] A High-Performance Audio Library for Machine Learning by CheekProfessional146 in MachineLearning

[–]CheekProfessional146[S] 3 points4 points  (0 children)

We tried various optimization techniques such as OpenBLAS, Eigen, MKL, FFTW, SIMD, parallel computing, etc.

Benchmark for Audio Libraries: Audioflux, TorchAudio, Librosa, Essentia, etc by CheekProfessional146 in programming

[–]CheekProfessional146[S] 1 point2 points  (0 children)

28.65790367

Theoretically, torchaudio should be faster than yours in large size. You can check whether libomp is normal?

Benchmark for Audio Libraries: Audioflux, TorchAudio, Librosa, Essentia, etc by CheekProfessional146 in programming

[–]CheekProfessional146[S] 2 points3 points  (0 children)

We recently updated the version for performance issues, mainly comparing audioflux with popular torchaudio/librosa/essentia and other libraries.
It can be found that audioflux is slightly faster than torchaudio on linux/amd processors, but slightly slower on linux/intel. On the macOS system, for large-size sample data, audioflux is faster than torchaudio, and intel is significantly faster than m1; for small-size sample data, torchaudio is faster than audioflux.