hearbenchmark / hear-baseline
Simple baseline model for the HEAR benchmark
☆22Updated last week
Related projects ⓘ
Alternatives and complementary repositories for hear-baseline
- Unsupervised Representation Learning for Singing Voice Separation☆21Updated last year
- A PyTorch implementation: "LASAFT-Net-v2: Listen, Attend and Separate by Attentively aggregating Frequency Transformation"☆33Updated 2 years ago
- A PyTorch implementation of the paper: "AMSS-Net: Audio Manipulation on User-Specified Sources with Textual Queries" (ACM Multimedia 2021…☆20Updated 3 years ago
- ☆32Updated 3 years ago
- Addressing the confounds of accompaniments in singer identification☆18Updated 4 years ago
- [ismir2019] Learning a Joint Embedding Space of Monophonic and Mixed Music Signals for Singing Voice☆27Updated last year
- Paderbox: A collection of utilities for audio / speech processing☆37Updated 4 months ago
- ☆17Updated 3 years ago
- ☆18Updated 5 years ago
- Backpropagable pytorch implementation of https://craffel.github.io/mir_eval/.☆35Updated 4 months ago
- Implementation of CREPE Pitch tracker with PyTorch☆19Updated 4 years ago
- Learning Complex Basis Functions for Invariant Signal Representations with the Complex Autoencoder☆34Updated 7 months ago
- ☆39Updated 4 years ago
- Unofficial PyTorch dataset for Slakh☆9Updated 3 years ago
- Audio samples for the paper "TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids"☆40Updated 4 years ago
- ☆21Updated 6 months ago
- A C++/Cython audio limiter for Python.☆23Updated last year
- Who calls the shots? Rethinking Few-Shot Learning for Audio (WASPAA 2021)☆40Updated 2 years ago
- ☆15Updated 2 years ago
- PodcastMix A dataset for separating music and speech in podcasts.☆43Updated 2 months ago
- Speech enhancement using mimic loss☆15Updated 5 years ago
- COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations☆48Updated 3 months ago
- J-Net is aimed for audio separation with randomly weighted encoder.☆10Updated 5 years ago
- acoss: Audio Cover Song Suite is a framework for feature extraction and benchmarking for the cover song identification (CSI) task☆37Updated last year
- PyTorch Dataset for Speech and Music audio☆73Updated 3 months ago
- Accompanying code for our paper "Optimizing Short-Time Fourier Transform Parameters via Gradient Descent"☆31Updated 4 years ago
- Audio activity detector based on per-channel energy normalization (PCEN)☆30Updated 5 years ago
- Multiple Fundamental Frequency Estimation☆26Updated 10 years ago
- Multipurpose Multi Speaker Mixture Signal Generator☆43Updated last month