| | --- |
| | 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 |
