--- license: cc-by-nc-sa-4.0 dataset_info: features: - name: id dtype: string - name: iso3 dtype: string - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 572226455183.244 num_examples: 221689 download_size: 569642045980 dataset_size: 572226455183.244 configs: - config_name: default data_files: - split: train path: data/train-* language: - aaa - aab - aac - aad - aaf - aai - aal - aao - aap - aar - aau - aaw - aaz - aba - abh - abi - abm - abn - abo - abr - abs - abt - abu - abz - aca - acd - ace - acf - ach - acm - acn - acq - acr - acu - acv - acw - acz - ada - add - ade - adh - adi - adj - adl - adn - ado - adq - adx - ady - adz - aeb - aec - aee - ael - aeu - aey - aez - afb - afe - afi - afo - afr - afu - afz - agb - agc - agd - age - agf - agg - agh - agi - agl - agn - agq - agr - ags - agt - agu - agw - agy - aha - ahb - ahg - ahk - ahl - ahp - ahr - ahs - aia - aif - aii - aik - aim - aio - aiw - aix - ajg - aji - akb - akc - akd - ake - akf - akg - 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xkl - xkn - xks - xkt - xkv - xky - xkz - xla - xmc - xmf - xmg - xmh - xmm - xmt - xmv - xmw - xmz - xnr - xns - xnz - xod - xog - xok - xom - xon - xpe - xra - xrb - xri - xrw - xsb - xsm - xsn - xsq - xsr - xsu - xta - xtc - xtd - xte - xti - xtj - xtl - xtm - xtn - xtt - xty - xub - xuj - xuu - xvi - xwe - xwg - xwl - yaa - yad - yae - yaf - yah - yak - yal - yam - yan - yao - yap - yaq - yaw - yax - yay - yaz - yba - ybb - ybe - ybh - ybi - ybj - ybl - ycl - ycn - ydd - yde - ydg - yea - yer - 'yes' - yet - yeu - yev - yey - ygr - ygw - yhd - yif - yig - yij - yim - yin - yiq - yis - yiu - yix - yiz - yka - ykg - yki - ykk - ykm - yle - yll - ymb - ymk - yml - ymm - yno - ynq - yns - yog - yom - yon - yor - yot - yoy - yra - yrb - yre - yrl - ysn - ysp - yss - yua - yue - yuf - yui - yuj - yum - yun - yup - yuq - yur - yuy - yuz - yva - ywa - ywl - ywn - ywq - yyu - zaa - zab - zac - zad - zae - zaf - zag - zai - zaj - zak - zam - zao - zap - zar - zas - zat - zau - zav - zaw - zay - zaz - zbc - zbu - zca - zcd - zdj - zeh - zem - zgb - zhi - zia - zik - zim - zin - ziw - zkd - zkn - zkr - zlj - zlm - zln - zmb - zmp - zmq - zms - zne - zng - zns - zoc - zoh - zom - zos - zpa - zpc - zpd - zpe - zpg - zph - zpj - zpk - zpl - zpm - zpn - zpo - zpp - zpq - zpr - zps - zpu - zpv - zpw - zpx - zpy - zpz - zrg - zro - zrs - zsm - zte - ztg - ztl - ztp - ztq - zts - ztx - zty - zua - zul - zun - zuy - zwa - zyb - zyg - zyj - zyn - zyp - zzj task_categories: - audio-to-audio - audio-classification --- MMS ulab v2 is a a massively multilingual speech dataset that contains **8900 hours** of unlabeled speech across **4023 languages**. In total, it contains 189 language families. It can be used for language identification, spoken language modelling, or speech representation learning. MMS ulab v2 is a reproduced and extended version of the MMS ulab dataset originally proposed in [Scaling Speech Technology to 1000+ Languages](https://arxiv.org/abs/2305.13516), covering more languages and containing more data. This dataset includes the raw unsegmented audio in a 16kHz single channel format. It can be segmented into utterances with a voice activity detection (VAD) model such as [this one](https://github.com/wiseman/py-webrtcvad). We use 6700 hours of MMS ulab v2 (post-segmentation) to train [XEUS](), a multilingual speech encoder for 4000+ languages. For more details about the dataset and its usage, please refer to our [paper](). ## License and Acknowledgement MMS ulab v2 is released under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license. If you use this dataset, we ask that you cite the following papers: ``` @article{pratap2024scaling, title={Scaling speech technology to 1,000+ languages}, author={Pratap, Vineel and Tjandra, Andros and Shi, Bowen and Tomasello, Paden and Babu, Arun and Kundu, Sayani and Elkahky, Ali and Ni, Zhaoheng and Vyas, Apoorv and Fazel-Zarandi, Maryam and others}, journal={Journal of Machine Learning Research}, volume={25}, number={97}, pages={1--52}, year={2024} } ``` And also reference [The Global Recordings Network](https://globalrecordings.net/en/copyright), the original source of the data.