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---
language:
- en
license: cc-by-4.0
dataset_info:
features:
- name: task
dtype: string
- name: subtask
dtype: string
- name: similarity
dtype: float64
- name: speaker_id
dtype: int64
- name: pair_id
dtype: int64
- name: audio_a
dtype:
audio:
sampling_rate: 16000
- name: audio_b
dtype:
audio:
sampling_rate: 16000
- name: sentence_a
dtype: string
- name: sentence_b
dtype: string
splits:
- name: test
num_bytes: 1713645707.328
num_examples: 2552
download_size: 1575109909
dataset_size: 1713645707.328
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# SpokenSTS Dataset
Spoken versions of the Semantic Textual Similarity dataset for testing semantic sentence level embeddings.
Contains thousands of sentence pairs annotated by humans for semantic similarity.
The spoken sentences can be used in sentence embedding models to test whether your model learns to capture sentence semantics.
## Disclaimer
**This distribution is not official.**
This subset only contains sentences from 4 human voices. Synthesized voices are excluded.
## Dataset structure
- There are five tasks: STS12 ~ STS16.
- Each tasks has couple of subtasks. Each subtask as few dozens of unique sentence pairs (numbers in parenthesis).
- STS12: MSRpar (38), MSRvid (38), SMTeuroparl (23), OnWN (43), SMTnews (20)
- STS13: FNWN (10), headlines (38), OnWN (30)
- STS14: deft-forum (23), deft-news (15), headlines (38), images (38), OnWN (32), tweet-news (38)
- STS15: answers-forums (19), answers-students (38), belief (19), headlines (38), images (38)
- STS16: answer-answer (13), headlines (13), plagiarism (12), postediting (13), question-question (11)
- Total 638 unique sentence pairs exist. Note that pair_id is only unique within the subtask.
- For each sentence pair, there are utterances from 4 speakers (speaker_id 1 ~ 4), total 638x4=2552 rows in the dataset.
- Sentence pair similarity ranges from minimum 0.0 to maximum 5.0.
- Refer Table 1 of SpokenSTS paper for more details on tasks & subtasks.
- Audio is resampled into 16kHz.
## References
- Original dataset and detailed metadata can be found at https://doi.org/10.17026/dans-z48-3ev6
- Codebase of SpokenSTS can be found at https://github.com/DannyMerkx/speech2image/tree/Interspeech21
- If you use the dataset, please cite:
- (Original STS database) Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Rada Mihalcea,
German Rigau, and Janyce Wiebe. Semeval-2016 task 1: Semantic textual similarity, monolingual
and cross-lingual evaluation. In SemEval, pages 497–511. ACL, 2016.
- (SpokenSTS) Danny Merkx, Stefan L. Frank and Mirjam Ernestus (2021). Semantic sentence similarity: size does
not always matter. In Interspeech 2021 - 22nd Annual Conference of the International Speech
Communication Association. pp. pp. 4393-4397 |