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metadata
annotations_creators:
  - expert-generated
license: cdla-permissive-1.0
language_creators:
  - expert-generated
size_categories:
  - 100M<n<100G
language:
  - en
task_categories:
  - automatic-speech-recognition
  - voice-activity-detection
multilinguality:
  - monolingual
task_ids: []
pretty_name: DipCo
tags:
  - speaker separation
  - speech-recognition
  - microphone array processing

DipCo - Dinner Party Corpus, Interspeech 2020

Only Download Dipco from Zenodo EU Open Link

wget --limit-rate=5m https://zenodo.org/record/8122551/files/DipCo.tgz?download=1
-czvf DipCo.tgz Dipco/

The ‘DipCo’ data corpus is a new data set that was publicly released by Amazon to help speech scientists address the difficult problem of separating speech signals in reverberant rooms with multiple speakers.

The corpus was created with the assistance of Amazon volunteers, who simulated the dinner-party scenario in the lab. We conducted multiple sessions, each involving four participants. At the beginning of each session, participants served themselves food from a buffet table. Most of the session took place at a dining table, and at fixed points in several sessions, we piped music into the room, to reproduce a noise source that will be common in real-world environments.

Each participant was outfitted with a headset microphone, which captured a clear, speaker-specific signal. Also dispersed around the room were five devices with seven microphones each, which fed audio signals directly to an administrator’s laptop. In each session, music playback started at a given time mark. The close-talk recordings were segmented and separately transcribed.

Sessions

Each session contains the close talk recordings of 4 participants and the far-field recordings from the 5 devices. The following name conventions are used:

  • sessions have a <session_id> label denoted by ```S01, S02, S03, ...``
  • participants have a <speaker_id> label denoted by P01, P02, P03, P04, ...
  • devices have a <device_id> label denoted by U01, U02, U03, U04, U05
  • array microphone have a <channel_id> label denoted by CH1, CH2, CH3, CH4, CH5, CH6, CH7

We currently have the following sessions:

Session Participants Hours [hh:mm] #Utts Music start [hh:mm:ss]
S01 P01, P02, P03, P04 00:47 903 00:38:52
S02 P05, P06, P07, P08 00:30 448 00:19:30
S03 P09, P10, P11, P12 00:46 1128 00:33:45
S04 P13, P14, P15, P16 00:45 1294 00:23:25
S05 P17, P18, P19, P20 00:45 1012 00:31:15
S06 P21, P22, P23, P24 00:20 604 00:06:17
S07 P21, P22, P23, P24 00:26 632 00:10:05
S08 P25, P26, P27, P28 00:15 352 00:01:02
S09 P29, P30, P31, P32 00:22 505 00:12:18
S10 P29, P30, P31, P32 00:20 432 00:07:10
The sessions have been split into a development and evaluation set as follows:
Dataset Sessions Hours [hh:mm] #Utts
Dev S02, S04, S05, S09, S10 02:43 3691
Eval S01, S03, S06, S07, S08 02:36 3619

The DiPCo data set has the following directory structure:

DiPCo/
├── audio	
│    ├── dev		
│    └── eval	
└── transcriptions	
      ├── dev		
      └── eval	

Audio

The audio data is converted into WAV format with a sample rate of 16kHz and 16-bit precision. The close-talk recordings were made by monaural microphone and contain a single channel. The far-field recordings of all 5 devices were microphone array recordings and contain 7 raw audio channels.

The WAV file name convention is as follows:

  • close talk recording of session <session_id> and participant <speaker_id>
    • <session_id>_<speaker_id>.wav, e.g. S01_P03.wav
  • farfield recording of microphone <channel_id> of session <session_id> and device <device_id>
    • <session_id>_<device_id>.<channel_id>.wav, e.g. S02_U3.CH1.wav

Transcriptions

Per session, a JSON format transcription file <session_id>.json has been provided. The JSON files contains for each transcribed utterance the following metadata:

  • Session ID ("session_id")

  • Speaker ID ("speaker_id")

    • Gender ("gender_id")
    • Mother Tongue ("mother_tongue")
    • Nativeness ("nativeness")
  • Transcription ("words")

  • Start time of utterance ("start_time")

    • The close-talk microphone recording of the speaker (close-talk)
    • The farfield microphone array recordings of devices with <device_id> label
  • End time ("end_time")

  • Reference signal that was used transcribing the audio ("ref")

The following is an example annotation of one utterance in a JSON file:

    {
      "start_time": {
            "U01": "00:02:12.79",
            "U02": "00:02:12.79",
            "U03": "00:02:12.79",
            "U04": "00:02:12.79",
            "U05": "00:02:12.79",
            "close-talk": "00:02:12.79"
        },
          "end_time": {
            "U01": "00:02:14.84",
            "U02": "00:02:14.84",
            "U03": "00:02:14.84",
            "U04": "00:02:14.84",
            "U05": "00:02:14.84",
            "close-talk": "00:02:14.84"
        },
        "gender": "male",
        "mother_tongue": "U.S. English",
        "nativeness": "native",
        "ref": "close-talk",
        "session_id": "S02",
        "speaker_id": "P05",
        "words": "[noise] how do you like the food"
    },

Transcriptions include the following tags:

  • [noise] noise made by the speaker (coughing, lip smacking, clearing throat, breathing, etc.)
  • [unintelligible] speech was not well understood by transcriber
  • [laugh] participant laughing

License Summary

The DiPCo data set has been released under the CDLA-Permissive license. See the LICENSE file.