---
license: cc-by-nc-4.0
task_categories:
- text-generation
language:
- en
tags:
- dialogue
pretty_name: Seamless Interaction Transcripts
size_categories:
- 1K<n<10K
---

# Seamless Interaction Transcripts

## Dataset Summary

**Seamless Interaction Transcripts** is a large-scale dialogue dataset derived from *facebook/seamless-interaction* dataset. It contains verbatim transcriptions of **>3k dialogues in English** covering a range of contexts from general chit-chat to customer service.

The dataset is designed to support research and development of speech and dialogue systems that require modeling of **conversational turn-taking**, such as real-time conversational agents.

---

## Source Data

* **Base datasets**: 
  - *facebook/seamless-interaction*
* **Language(s)**: English
* **Modality**: Text
* **Interaction type**: Human conversational speech
* **Dialogues**: 3335
* **Avg. Turns / Dialogue**: 37.47
* **Speakers**: 2000+

Dataset splits (e.g., train/validation/test) are not predefined and may be created by downstream users as needed. Deduplication was applied to the underlying text sources to ensure dataset splits can be made without contamination.

---

## Annotation Details

* **Transcripts**

  * Generated automatically using **Whisper Large V3 Turbo**.
  * A subset of samples (\~200) was manually reviewed. The transcripts are estimated to have approximately a word error rate (WER) of **\~2.8%**.
    
---

## Dataset Structure

A typical data entry includes:

* `interaction_id`: Identifier for the interaction
* `messages`: Transcriptions in the form of an OpenAI-compatible chat message buffer
* `relation`: High level relationship identifier, e.g. "strangers", "familiar"
* `relation_detailed`: Detailed relationship identifier, e.g. "coworkers", "spouse"

---

## Usage
In order to load the dataset from the hub, you can use the `datasets` library:

```python
ds = datasets.load_dataset(
    "ThBel/seamless-interaction-transcripts",
    split='train',
    streaming=True # (optional)
)

for row in ds:
    # Do something with the data
    print(row['messages'])
```

Alternatively you may clone the `ThBel/seamless-interaction-transcripts` repository, and load the underlying parquet files using `pandas.read_parquet`.

---

## Disclaimer and Licensing

Note that Seamless Interaction Transcripts is a *derived dataset*. I am not the original creator of the source dataset (facebook/seamless-interaction) and hold no rights over its content. This dataset is provided as-is for research purposes, and all credit goes to the original authors.

Annotations are released under the **CC-BY-NC 4.0** license and are intended to be compatible with the licensing terms of the source dataset. 

---

## Citation

If you use the Seamless Interaction Transcripts dataset in academic, non-commercial work, please reference the original dataset.