File size: 1,232 Bytes
0d1a388 646da3a d553493 646da3a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
---
dataset_info:
features:
- name: audio_a
dtype: audio
- name: audio_b
dtype: audio
- name: label
dtype: string
- name: text_a
dtype: string
- name: text_b
dtype: string
- name: human_quality_a
dtype: float64
- name: human_quality_b
dtype: float64
- name: system_a
dtype: string
- name: system_b
dtype: string
splits:
- name: train
num_bytes: 241032306.0
num_examples: 600
download_size: 221703663
dataset_size: 241032306.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Speech Quality Assessment Data
The dataset is derived from the TMHINT-Q dataset [(paper)](https://arxiv.org/pdf/2111.02585). The speech is in Mandarin Chinese, and noise of different types and levels was added to clean speech.
Human annotators were asked to score each audio on its "quality" aspect on a 1-5 scale (shown in `human_quality_a/b` is the average across multiple annotators). Note that the full pairwise mapped dataset contains 6475, and for this work we sample 600 rows.
- `label = a` => `audio_a` is of higher quality than `audio_b` (i.e., less noisy and clearer)
- `label = b` => `audio_b` is of higher quality than `audio_a` |