README.md

---

pretty_name: "PC-Mix"
language:
  - en
task_categories:
  - audio-classification
tags:
  - audio
  - anti-spoofing
  - partially-spoofed-audio
  - environmental-sounds
license: other
---


# PC-Mix Dataset

**Partial Spoof Dataset with Controlled Speech–Environmental Sounds Mixing**

PC-Mix pairs speech from **PartialSpoof v1.2** with a **self-curated partial-spoof environmental sounds pool** to create controlled speech–environment authenticity combinations. The **original** samples are collected from **VGGSound** and **SBCSAE**.

## Resources

| Resource | Description | Link |
|---|---|---|
| GitHub | Code, protocols, and preprocessing scripts. | [Anonymous GitHub](https://anonymous.4open.science/r/PC-Mix-3AFE/README.md) |
| Paper | Dataset description and baselines. | PDF / arXiv (TBD) |
| Hugging Face | Dataset card and hosted files. | [HF Dataset](https://huggingface.co/datasets/Alphawarheads/PC-Mix) |
| Download | Direct access to the packaged dataset files. | [Download Files](https://huggingface.co/datasets/Alphawarheads/PC-Mix/tree/main) |

## Download and Setup

PC-Mix is hosted on Hugging Face under `Alphawarheads/PC-Mix`. The dataset directories are compressed with `tar` and `zstd`, then split into fixed-size volumes for more convenient downloading. All archive parts belonging to the same directory must be downloaded before extraction.

### Option 1: Download with Hugging Face CLI

```bash

pip install -U "huggingface_hub[cli]"



huggingface-cli download Alphawarheads/PC-Mix \

  --repo-type dataset \

  --local-dir ./PC-Mix

```

### Option 2: Clone with Git LFS

```bash

git lfs install



git clone https://huggingface.co/datasets/Alphawarheads/PC-Mix

```

### Option 3: Access from Python

```python

from huggingface_hub import snapshot_download



snapshot_download(

    repo_id="Alphawarheads/PC-Mix",

    repo_type="dataset",

    local_dir="./PC-Mix",

)

```

### Install the extraction dependency

The archive volumes use Zstandard compression.

Using Conda:

```bash

conda install -c conda-forge zstd

```

Using Ubuntu/Debian:

```bash

sudo apt install zstd

```

## Packaged File Structure

The files hosted on Hugging Face are organized as follows:

```text

PC-Mix/

├── README.md

├── buildSBCori.py

├── extract_orig_from_mixed_protocol.py

├── FILELIST.txt

├── SHA256SUMS

│

├── Mixed_soundsV1.2/

│   ├── Mixed_soundsV1.2.tar.zst.part-000

│   ├── Mixed_soundsV1.2.tar.zst.part-001

│   ├── Mixed_soundsV1.2.tar.zst.part-002

│   └── ...

│

└── Partialspoof_background/

    ├── Partialspoof_background.tar.zst.part-000

    ├── Partialspoof_background.tar.zst.part-001

    └── ...

```

The split volumes preserve the original directory names and all internal relative paths. After extraction, the dataset returns to the directory structure described in [Dataset Structure](#dataset-structure).

### Verify downloaded volumes

Run the checksum verification from the downloaded repository root:

```bash

cd ./PC-Mix

sha256sum -c SHA256SUMS

```

Every successfully downloaded volume should be reported as `OK`.

## Extract the Split Archives

Create a destination directory:

```bash

mkdir -p ./PC_Mix_extracted

```

### Extract `Mixed_soundsV1.2`



```bash

cat ./PC-Mix/Mixed_soundsV1.2/Mixed_soundsV1.2.tar.zst.part-* \

  | zstd -dc \

  | tar -xf - -C ./PC_Mix_extracted

```



### Extract `Partialspoof_background`

```bash

cat ./PC-Mix/Partialspoof_background/Partialspoof_background.tar.zst.part-* \

  | zstd -dc \

  | tar -xf - -C ./PC_Mix_extracted

```

After extraction:

```text

PC_Mix_extracted/

├── Mixed_soundsV1.2/

└── Partialspoof_background/

```

Do not rename, individually decompress, or extract the `.part-*` files. They are consecutive parts of a single compressed archive and must be concatenated in numerical order.

## Reconstruct the SBCSAE-Derived Original WAV Files

Due to the **CC BY-ND 3.0 US** license of SBCSAE, SBCSAE-derived cropped audio is not directly redistributed in PC-Mix. The repository provides the protocols and preprocessing scripts required to reconstruct these files locally after obtaining the official SBCSAE WAV data.

The reconstruction workflow uses:

- `extract_orig_from_mixed_protocol.py`
- `buildSBCori.py`
- the extracted `Mixed_soundsV1.2` directory
- the official SBCSAE `WAV` directory

### 1. Remove SBCSAE-derived original files before redistribution

This command identifies SBCSAE-derived original entries through the mixed-data protocols and deletes their corresponding `train_orig_*` or `eval_orig_*` WAV files.

```bash

python extract_orig_from_mixed_protocol.py \

  --mixed_sounds_dir /dkucc/home/zz324/Audiodata/PC_Mix/Mixed_soundsV1.2 \

  --delete

```

This step is primarily used when preparing a redistributable release. Users downloading the public PC-Mix package normally receive a version in which these restricted files have already been removed.

### 2. Reconstruct the omitted WAV files locally

After downloading the official SBCSAE audio and placing its WAV files under a local `WAV` directory, run:

```bash

python buildSBCori.py \

  --input_dir /dkucc/home/zz324/Audiodata/WAV \

  --mixed_sounds_dir /dkucc/home/zz324/Audiodata/PC_Mix/Mixed_soundsV1.2 \

  --protocol_ref /dkucc/home/zz324/Audiodata/PC_Mix/Mixed_soundsV1.2 \

  --overwrite

```

Arguments:

- `--input_dir`: directory containing the officially obtained SBCSAE WAV files.
- `--mixed_sounds_dir`: extracted `Mixed_soundsV1.2` directory in which the reconstructed original files will be written.
- `--protocol_ref`: directory containing the train and evaluation protocols used to locate the required SBCSAE source segments.
- `--overwrite`: regenerate target files even when files with the same names already exist.

The script reconstructs the omitted SBCSAE-derived original clips while preserving the expected PC-Mix file names and directory layout.

## Audio Class Description

PC-Mix provides both utterance-level and frame-level annotations.

At the utterance level, each sample is assigned to one of five classes: one class for original real-world recordings and four classes for constructed mixtures with different speech/environmental-sound authenticity combinations.

At the frame level, PC-Mix focuses on constructed mixtures only. Each frame is assigned to one of four classes based on whether the speech component, the environmental-sound component, or both components are spoofed at that time.

### Utterance-Level Classes

| Class | Name | Speech | Environmental Sounds | Description |
|---:|---|---|---|---|
| 0 | Original | — | — | A naturally recorded audio clip containing speech and environmental sounds, without artificial speech–environment mixing. |
| 1 | Bona fide + Bona fide | Bona fide | Bona fide | A constructed mixture where both the speech component and the environmental-sound component are bona fide. |
| 2 | Spoofed + Bona fide | Spoofed | Bona fide | A constructed mixture containing partially spoofed speech while the environmental-sound component remains bona fide. |
| 3 | Bona fide + Spoofed | Bona fide | Spoofed | A constructed mixture containing bona fide speech with partially spoofed environmental sounds. |
| 4 | Spoofed + Spoofed | Spoofed | Spoofed | A constructed mixture where both speech and environmental sounds contain partially spoofed regions. |

### Frame-Level Classes

| Class | Name | Speech | Environmental Sounds | Description |
|---:|---|---|---|---|
| 0 | Bona fide frame | Bona fide | Bona fide | Neither component is spoofed in this frame. |
| 1 | Speech-spoofed frame | Spoofed | Bona fide | The local spoofing occurs in the speech component only. |
| 2 | Environmental-sound-spoofed frame | Bona fide | Spoofed | The local spoofing occurs in the environmental-sound component only. |
| 3 | Both-spoofed frame | Spoofed | Spoofed | Both speech and environmental sounds are spoofed in this frame. |

## Dataset Structure

After the split archives have been extracted and the omitted SBCSAE-derived original clips have been reconstructed, the dataset follows this structure:

```text

PC_Mix

├── README.md

│

├── Mixed_soundsV1.2                                  # mixed speech + environmental sounds audio

│   │

│   ├── train                                         # training split

│   │   ├── protocol.txt                              # mapping from mixed audio to source speech/environmental sounds

│   │   ├── wav                                       # mixed audio files, e.g., train_mix_0000000.wav

│   │   └── labels                                    # NumPy label files

│   │       ├── speech                                # speech-component segment labels

│   │       ├── env                                   # environmental-sounds component segment labels

│   │       ├── mix                                   # mixture-level segment labels

│   │       └── original_vs_others_seglab             # original-vs-non-original segment labels

│   │

│   ├── eval                                          # evaluation split

│   │   ├── protocol.txt                              # mapping from mixed audio to source speech/environmental sounds

│   │   ├── wav                                       # mixed audio files, e.g., eval_E0_mix_0000006.wav

│   │   └── labels                                    # NumPy label files

│   │       ├── speech

│   │       ├── env

│   │       ├── mix

│   │       └── original_vs_others_seglab

│   │

│   ├── label_PartialSpoof_train                      # text-format PartialSpoof-style labels for training

│   │   ├── wav-train.scp

│   │   ├── original_vs_others_utt_labels.txt

│   │   ├── speech                                    # train_protocol_*.txt

│   │   ├── env                                       # train_protocol_*.txt

│   │   ├── mix                                       # train_protocol_*.txt

│   │   └── original_vs_others_seglab                 # train_protocol_*.txt

│   │

│   └── label_PartialSpoof_eval                       # text-format PartialSpoof-style labels for evaluation

│       ├── wav-eval.scp

│       ├── original_vs_others_utt_labels.txt

│       ├── speech                                    # eval_protocol_*.txt

│       ├── env                                       # eval_protocol_*.txt

│       ├── mix                                       # eval_protocol_*.txt

│       └── original_vs_others_seglab                 # eval_protocol_*.txt

│

└── Partialspoof_background                           # source environmental sounds data

    │

    ├── train                                         # training environmental sounds split

    │   ├── protocol.txt                              # environmental sounds audio protocol

    │   ├── wav                                       # environmental sounds audio files

    │   └── labels                                    # segment labels in .npy/.txt formats

    │

    ├── eval                                          # evaluation environmental sounds split

    │   ├── protocol.txt                              # environmental sounds audio protocol

    │   ├── wav                                       # environmental sounds audio files

    │   └── labels                                    # segment labels in .npy/.txt formats

    │

    ├── label_PartialSpoof_train                      # text-format environmental sounds labels for training

    │   └── train_protocol_*.txt

    │

    └── label_PartialSpoof_eval                       # text-format environmental sounds labels for evaluation

        └── eval_protocol_*.txt

```

## Audio Source

| Component | Source | Description |
|---|---|---|
| Speech | PartialSpoof v1.2 | Speech samples with partially spoofed speech annotations. |
| Environmental Sounds | Self-curated partial-spoof environmental sounds pool | Environmental sounds with controlled bona fide/spoofed component labels. |
| Original | VGGSound and SBCSAE | Original recordings without artificial speech–environment mixing. |

## Data Splits

### Training Set

| Split | Mixed Samples | Original Samples | Environmental Sounds Source | Event Source | Fusion Method |
|---|---:|---:|---|---|---|
| Train | 25,380 | 12,155 | SONYC | 60% AudioLDM2; 40% UrbanSound8K (0–1 s) | Ducking Overlay |

### Evaluation Sets

| Subset | Mixed | Original | Environmental Sounds | Event | Fusion |
|---|---:|---:|---|---|---|
| E0 Baseline | 17,812 | 17,809 | SONYC | 60% AudioLDM2; 40% FSD50K (0–1 s) | Ducking Overlay |
| E1 Generator OOD | 14,248 | — | SONYC | AudioGen | Ducking Overlay |
| E2 Fusion OOD | 14,248 | — | SONYC | AudioLDM2 | Energy Matching + Crossfade (20–80 ms) |
| E3 Environmental Sounds OOD | 17,809 | — | DEMAND | AudioLDM2 | Ducking Overlay |
| E4 Noise OOD | 7,125 | — | WHAM Noise | AudioLDM2 | Ducking Overlay |

## Metadata

Each mixed sample is associated with a protocol entry that records its mixed-audio ID, speech source, environmental sounds source, mixing duration, SNR, gain/scaling information, and offset information.

Example:

```text

train_mix_0000000 mix CON_T_0000000.wav train_29_006663_s2.wav 1.000 1.400 snr_db=8.000 bg_scale=0.425705 offset_sec=0.909625 offset_samp=14554

```

## Citation

<!-- Citation information will be added after publication. -->

## License 🔐

PC-Mix is released for non-commercial research purposes. Part of this dataset is a derived dataset constructed by combining, mixing, cropping, and generating audio samples from multiple publicly available datasets and audio generation models. Users must comply with the original licenses of all upstream datasets and models.

- The [PartialSpoof](https://zenodo.org/records/5112031), [VGGSound](https://www.robots.ox.ac.uk/~vgg/data/vggsound/), and [SONYC-UST](https://zenodo.org/records/3966543) datasets are released under the CC BY 4.0 license.

- The [UrbanSound8K](https://zenodo.org/records/1203745) and [WHAM!](https://wham.whisper.ai/) noise data are released under the CC BY-NC 4.0 license.

- The [FSD50K](https://zenodo.org/records/4060432) dataset contains audio clips under multiple Creative Commons licenses, including CC0, CC BY, CC BY-NC, and CC Sampling+. Users should follow the per-clip license metadata provided by FSD50K.

- The [DEMAND](https://zenodo.org/records/1227121) dataset is released under the CC BY-SA 3.0 license.

- The synthetic environmental event sounds generated by [AudioLDM2](https://huggingface.co/cvssp/audioldm2) are produced using model weights released under the CC BY-NC-SA 4.0 license.

- The synthetic environmental event sounds generated by [AudioGen](https://huggingface.co/facebook/audiogen-medium) are produced using model weights released under the CC BY-NC 4.0 license.

- The [SBCSAE / Santa Barbara Corpus of Spoken American English](https://www.openslr.org/155/) is released under the CC BY-ND 3.0 US license. Due to the NoDerivatives condition, SBCSAE-derived audio clips are not directly redistributed in PC-Mix. We only provide the official download link, segment-level metadata, and preprocessing scripts so that users who have obtained SBCSAE from the official source can reproduce this subset locally.

> **Important:** PC-Mix does not override the licenses of the original datasets or models. By using PC-Mix, users agree to comply with all upstream license terms.

## Contact Information

<!-- Contact information will be added after the anonymous review period. -->