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---
license: apache-2.0
dataset_info:
features:
- name: audio
dtype: audio
- name: transcript_annotated
dtype: string
- name: transcript_a
dtype: string
- name: transcript_b
dtype: string
- name: transcript_c
dtype: string
splits:
- name: train
num_bytes: 1343263191.5
num_examples: 4500
- name: validation
num_bytes: 75479207.0
num_examples: 250
- name: test
num_bytes: 72139425.0
num_examples: 250
download_size: 1482840572
dataset_size: 1490881823.5
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
# DisfluencySpeech Dataset
The DisfluencySpeech Dataset is a single-speaker studio-quality labeled English speech dataset with paralanguage.
A single speaker recreates nearly 10 hours of expressive utterances from the Switchboard-1 Telephone Speech Corpus
(Switchboard), simulating realistic informal conversations. To aid the development of a text-to-speech (TTS) model that is able to
predictively synthesise paralanguage from text without such components, we provide three different transcripts at
different levels of information removal (removal of non-speech events, removal of non-sentence elements,
and removal of false starts).
Read the paper [here](https://arxiv.org/abs/2406.08820).
Benchmark TTS models for each transcript can be found here: [Transcript A](https://huggingface.co/amaai-lab/DisfluencySpeech_BenchmarkA), [Transcript B](https://huggingface.co/amaai-lab/DisfluencySpeech_BenchmarkB), and [Transcript C](https://huggingface.co/amaai-lab/DisfluencySpeech_BenchmarkC).
# Dataset Details
All audio files are provided as 22,050 hz _.wav_ files. In the _metadata.csv_ file, 4 different transcripts for each file are provided,
each at differing levels of information removal:
- _transcript_annotated_ is a full transcript retaining all non-speech event and disfluency annotations;
- _transcript_a_ contains all textual content recorded, including non-sentence elements and restarts. Only non-speech events such as laughter and sighs are removed from transcript;
- _transcript_b_ is _transcript_a_ but with filled pauses, explicit editing terms, and discourse markers removed. Coordinating conjunctions and asides are left in, as they are non-sentence elements as well, they are often used to convey meaning; and
- _transcript_c_ is _transcript_b_ but with false starts removed. This is the most minimal transcript.
The training set contains 90% of the data, the validation set contains 5% of the data, and the test set contains 5% of the data.
# Citation
If you use this dataset, please cite the paper in which it is presented:
```
@misc{wang2024disfluencyspeechsinglespeakerconversational,
title={DisfluencySpeech -- Single-Speaker Conversational Speech Dataset with Paralanguage},
author={Kyra Wang and Dorien Herremans},
year={2024},
eprint={2406.08820},
archivePrefix={arXiv},
primaryClass={eess.AS},
url={https://arxiv.org/abs/2406.08820},
}
``` |