Data · dataset · 2023
Unlabelled Arabic Speech Dataset
Listed in Teesside University Research Data Repository
Speech is crucial for communication, especially in the era of artificial intelligence.
Description
Many fields, including security and forensics, rely on analyzing speech, where it can be used to identify people, but there's a challenge when it comes to Arabic language data. Most speech analysis models are primarily trained on English data and don't work well with Arabic.
Therefore, a large dataset with over a million Arabic samples was built for training models and improving performance. The samples were collected from Arabic podcasts, so they're clear and noise-free. The audio recordings were extracted and segmented into one-second segments.
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Then, they were transformed into Mel-spectrograms, using a 22 kHz sampling rate, a frame size of 2048 samples, and a hop length of 512 samples. Researchers working with Arabic speech data can benefit from this dataset to try different machine learning and deep learning models. Using our dataset to improve Arabic speaker identification, we trained a Siamese speech embedding model.
We tested its performance using a benchmark dataset, which can be viewed in the paper titled "Unsupervised Arabic Speech Embedding Model for Speaker Identification" ieeexplore-ieee-org.aus.idm.oclc.org/document/10191576.
Links
Where it is published
- DOI doi.org/10.17632/yhy76b2c7b.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Deep learning · Earth & Environmental Science · Humanities · Signal processing
- Inferred from text
- Audio 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/yhy76b2c7b.1 | 7 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:400607 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Signal Processing'] |
| concepts[field].anzsrc:field:461103 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Deep Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:audio | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |