---
dataset_info:
- config_name: deu
  features:
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: timestamps_start
    sequence: float64
  - name: timestamps_end
    sequence: float64
  - name: speakers
    sequence: string
  splits:
  - name: data
    num_bytes: 2124232888
    num_examples: 120
  download_size: 2089622461
  dataset_size: 2124232888
- config_name: eng
  features:
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: timestamps_start
    sequence: float64
  - name: timestamps_end
    sequence: float64
  - name: speakers
    sequence: string
  splits:
  - name: data
    num_bytes: 2338819328
    num_examples: 140
  download_size: 2298491715
  dataset_size: 2338819328
- config_name: jpn
  features:
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: timestamps_start
    sequence: float64
  - name: timestamps_end
    sequence: float64
  - name: speakers
    sequence: string
  splits:
  - name: data
    num_bytes: 2159798942
    num_examples: 120
  download_size: 2119318800
  dataset_size: 2159798942
- config_name: spa
  features:
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: timestamps_start
    sequence: float64
  - name: timestamps_end
    sequence: float64
  - name: speakers
    sequence: string
  splits:
  - name: data
    num_bytes: 2456735672
    num_examples: 140
  download_size: 2424929812
  dataset_size: 2456735672
- config_name: zho
  features:
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: timestamps_start
    sequence: float64
  - name: timestamps_end
    sequence: float64
  - name: speakers
    sequence: string
  splits:
  - name: data
    num_bytes: 2336018713
    num_examples: 140
  download_size: 2307711237
  dataset_size: 2336018713
configs:
- config_name: deu
  data_files:
  - split: data
    path: deu/data-*
- config_name: eng
  data_files:
  - split: data
    path: eng/data-*
- config_name: jpn
  data_files:
  - split: data
    path: jpn/data-*
- config_name: spa
  data_files:
  - split: data
    path: spa/data-*
- config_name: zho
  data_files:
  - split: data
    path: zho/data-*
license: cc-by-nc-sa-4.0
language:
- en
- ja
- zh
- de
- es
tags:
- speaker-diarization
- speaker-segmentation
- voice-activity-detection
extra_gated_fields:
  Company: text
  Country: country
---


# Dataset Card for the Callhome dataset for speaker diarization

The CALLHOME Corpus is a collection of unscripted telephone conversations between native speakers in Chinese, English, German, Japanese and Spanish. 

This is a processed version of the original Callhome dataset from the TalkBank corpora taken from [here](https://ca.talkbank.org/access/CallHome/
). It contains subsets in Chinese, English, German, Japanese and Spanish: 

- More information on the [Chinese subset](https://ca.talkbank.org/access/CallHome/zho.html)
- More information on the [English subset](https://ca.talkbank.org/access/CallHome/eng.html)
- More information on the [German subset](https://ca.talkbank.org/access/CallHome/deu.html)
- More information on the [Japanese subset](https://ca.talkbank.org/access/CallHome/jpn.html)
- More information on the [Spanish subset](https://ca.talkbank.org/access/CallHome/spa.html)

Note: This dataset has been processed using [diarizers](https://github.com/huggingface/diarizers/tree/main/datasets). It makes the dataset compatible with the diarizers library to fine-tune [pyannote](https://huggingface.co/pyannote/segmentation-3.0) segmentation models. 
In particular, we only keep the annotated parts of the callhome dataset. For more information on how the dataset has been processed, refer to diarizers. 


# Example Usage

```
from datasets import load_dataset
ds = load_dataset("diarizers-community/callhome", "jpn")
print(ds)
```


gives:

```
DatasetDict({
    train: Dataset({
        features: ['audio', 'timestamps_start', 'timestamps_end', 'speakers'],
        num_rows: 120
    })
})
```

# Dataset source and citation: 

[Chinese Corpus](https://ca.talkbank.org/access/CallHome/zho.html): 

- Participants:	140
- Type of Study:	phone call
- Location:	China
- Media type:	audio
- DOI:	doi:10.21415/T54022

[English](https://ca.talkbank.org/access/CallHome/eng.html)


- Participants:	120
- Type of Study:	naturalistic
- Location:	USA
- Media type:	audio
- DOI:	doi:10.21415/T5KP54

[German](https://ca.talkbank.org/access/CallHome/deu.html)

- Participants:	100
- Type of Study:	phone call
- Location:	United States
- Media type:	audio
- DOI:	doi:10.21415/T56P4B

[Japanese](https://ca.talkbank.org/access/CallHome/jpn.html)

- Participants:	120
- Type of Study:	phone call
- Location:	United States
- Media type:	audio
- DOI:	doi:10.21415/T5H59V

[Spanish](https://ca.talkbank.org/access/CallHome/spa.html)

- Participants:	120
- Type of Study:	phone call
- Location:	United States
- Media type:	audio
- DOI:	doi:10.21415/T51K54

# Contribution

Thanks to [@kamil-akesbi](https://huggingface.co/kamilakesbi) and [sanchit-gandhi](https://huggingface.co/sanchit-gandhi) for the contribution.