| --- |
| license: cc-by-4.0 |
| dataset_info: |
| features: |
| - name: audio |
| dtype: audio |
| - name: name |
| dtype: string |
| configs: |
| - config_name: default |
| data_files: |
| - split: speech_english |
| path: data/speech-english-*.parquet |
| - split: speech_french |
| path: data/speech-french-*.parquet |
| - split: speech_german |
| path: data/speech-german-*.parquet |
| - split: speech_italian |
| path: data/speech-italian-*.parquet |
| - split: speech_russian |
| path: data/speech-russian-*.parquet |
| - split: speech_spanish |
| path: data/speech-spanish-*.parquet |
| - split: noise |
| path: data/noise-*.parquet |
| - split: rir_slr26 |
| path: data/rir-slr26-*.parquet |
| - split: rir_slr28 |
| path: data/rir-slr28-*.parquet |
| --- |
| |
| # DNS5 Challenge data |
|
|
| This is a mirror of the [DNS5 Challenge data](https://github.com/microsoft/DNS-Challenge/). |
| The original files were converted from WAV to Opus to reduce the size and accelerate streaming. |
|
|
| ⚠️ Only the LibriVox, AudioSet, Freesound, OpenSLR26, and OpenSLR28 data is included. The VCTK, VocalSet, CREMA-D, VoxCeleb2, and DEMAND data is excluded. ⚠️ |
|
|
| - **Sampling rate**: 48 kHz |
| - **Channels**: 1 |
| - **Format**: Opus |
| - **Splits**: |
| - **speech_english**: 245 hours, 186743 files |
| - **speech_french**: 95 hours, 60454 files |
| - **speech_german**: 137 hours, 119175 files |
| - **speech_italian**: 70 hours, 59525 files |
| - **speech_russian**: 25 hours, 16566 files |
| - **speech_spanish**: 86 hours, 78603 files |
| - **noise**: 177 hours, 63810 files |
| - **rir_slr26**: 17 hours, 60000 files |
| - **rir_slr28**: 0.1 hours, 248 files |
| - **License:** |
| - **LibriVox**: [Public domain](https://librivox.org/pages/public-domain/) |
| - **AudioSet**: CC BY 4.0 |
| - **Freesound**: CC0 1.0 |
| - **OpenSLR26 and OpenSLR28**: Apache 2.0 |
| - **Source:** [https://github.com/microsoft/DNS-Challenge/](https://github.com/microsoft/DNS-Challenge/) |
| - **Paper:** [ICASSP 2023 Deep Noise Suppression Challenge](https://arxiv.org/abs/2303.11510) |
|
|
| ## Usage |
|
|
| ```python |
| import io |
| |
| import soundfile as sf |
| from datasets import Features, Value, load_dataset |
| |
| for item in load_dataset( |
| "philgzl/dns5", |
| split="speech_english", |
| streaming=True, |
| features=Features({"audio": Value("binary"), "name": Value("string")}), |
| ): |
| print(item["name"]) |
| buffer = io.BytesIO(item["audio"]) |
| x, fs = sf.read(buffer) |
| # do stuff... |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{dubey2024icassp, |
| title = {{ICASSP} {2023} {Deep} {Noise} {Suppression} {Challenge}}, |
| author = {Dubey, Harishchandra and Aazami, Ashkan and Gopal, Vishak and Naderi, Babak and Braun, Sebastian and Cutler, Ross and Gamper, Hannes and Golestaneh, Mehrsa and Aichner, Robert}, |
| journal = {IEEE Open J. Signal Process.}, |
| volume = {5}, |
| pages = {725--737}, |
| year = {2024}, |
| } |
| ``` |
|
|
