license:mit size_categories:1M<n<10M format:parquet modality:audio modality:text library:datasets library:dask library:mlcroissant library:polars region:us
---
license: mit
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: Speaker_Id
    dtype: string
  - name: SYSTEM_ID
    dtype: string
  - name: KEY
    dtype: string
  - name: Laundering_Type
    dtype: string
  - name: Laundering_Param
    dtype: string
  splits:
  - name: train
    num_bytes: 137488557853.713
    num_examples: 2065873
  download_size: 106529597527
  dataset_size: 137488557853.713
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

========================================================================================================

ASVspoof Laundered Database: This database is based on ASVspoof 2019 logical access (LA) eval partition.

The Asvspoof 2019 LA eval database is passed through five different types of additive noise at three 
different Signal-to-Noise ratio (SNR) levels, three types of reverberation noise, six different re-compression rates, four 
different resampling factors, and one type of low pass filtering accumulating to a total of 1388.22 
hours of audio data.

Dataset Creators: Hashim Ali, Surya Subramani, Shefali Sudhir, Raksha Varahamurthy and Hafiz Malik

Dataset Contact: Hashim Ali alhashim@umich.edu

Date Written: 05/29/2024

*** WARNING ***

The 'flac' folder contains over 2 million (2065873) files. Open this folder at your own risk.

========================================================================================================


1. Directory Structure

--> ASVspoofLauneredDatabase
    
    --> flac
   
    --> protocols
	
    --> Readme.txt

_________________________________

2. Description of the audio files

    The directory flac contain audio files for each type of laundering attack, namely, Noise_Addition, Reverberation, Recompression, Resampling, and Filtering. Each laundering
    attack (i) has different parameters (j) which are described below in the protocols section. All audio files in this directory are in the flac format.

_______________________________

3. Description of the protocols

    The directory protocols contains five protocol files, one for each laundering attack. 

    Each column of the protocol is formatted as:
    
        SPEAKER_ID      AUDIO_FILE_NAME      SYSTEM_ID KEY      Laundering_Type      Laundering_Param
    
        1) SPEAKER_ID: 		    LA_****, a 4-digit speaker ID
        2) AUDIO_FILE_NAME: 	LA_****, name of the audio file
        3) SYSTEM_ID: 		    ID of the speech spoofing system (A01 - A19),  or, for bonafide speech   SYSTEM-ID is left blank ('-')
        4) KEY: 		        'bonafide' for genuine speech, or, 'spoof' for spoofing speech
        5) Laundering_Type      Type of laundering attack. One of 'Noise_Addition', 'Reverberation', 'Recompression', 'Resampling', and 'Filtering'
        6) Laundering_Param     Parameters for the laundering attack. For example, in the case of Noise_Addition, it can be 'babble_0' where babble is the type of additive noise and 0 is the SNR level at which the babble noise is added to the audio signal.

    **Note that**: 
   
   	1) the first four columns are the same as in ASVspoof2019_LA_cm_protocols (refer to the ASVspoof2019 database), where the fourth in the original database
        is omitted since it is NOT used for LA.
   	2) Brief description on the Laundering_Param:

        babble_0                    babble noise at SNR level of 0
        babble_10                   babble noise at SNR level of 10
        babble_20                   babble noise at SNR level of 20
        cafe_0                      cafe noise at SNR level of 0
        cafe_10                     cafe noise at SNR level of 10
        cafe_20                     cafe noise at SNR level of 20
        street_0                    street noise at SNR level of 0
        street_10                   street noise at SNR level of 10
        street_20                   street noise at SNR level of 20
        volvo_0                     volvo noise at SNR level of 0
        volvo_10                    volvo noise at SNR level of 10
        volvo_20                    volvo noise at SNR level of 20
        white_0                     white noise at SNR level of 0
        white_10                    white noise at SNR level of 10
        white_20                    white noise at SNR level of 20
        RT_0_3                      Reverberation with RT60 = 0.3 sec
        RT_0_6                      Reverberation with RT60 = 0.6 sec
        RT_0_9                      Reverberation with RT60 = 0.9 sec
        recompression_128k          Compression using bit rate of 128 kbit/s
        recompression_16k           Compression using bit rate of 16 kbit/s
        recompression_196k          Compression using bit rate of 196 kbit/s
        recompression_256k          Compression using bit rate of 256 kbit/s
        recompression_320k          Compression using bit rate of 320 kbit/s
        recompression_64k           Compression using bit rate of 64 kbit/s
        resample_11025              resampling rate of 11025 Hz
        resample_22050              resampling rate of 22050 Hz
        resample_44100              resampling rate of 44100 Hz
        resample_8000               resampling rate of 8000 Hz
        lpf_7000                    low pass filtering with a cut-off frequency of 7 Khz

**Citation**
```
@inproceedings{ali2024audio,
  title={Is Audio Spoof Detection Robust to Laundering Attacks?},
  author={Ali, Hashim and Subramani, Surya and Sudhir, Shefali and Varahamurthy, Raksha and Malik, Hafiz},
  booktitle={Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security},
  pages={283--288},
  year={2024}
}
```