---
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`