--- license: cc0-1.0 task_categories: - text-to-speech - automatic-speech-recognition language: - en - de - fr - bg - ar pretty_name: Mumospee_small tags: - Speech - Video --- # Mumospee: A MUltiMOdal SPEEch Corpus (small) This is a small version of Mumospee include no more 1000 rows. The full is [here](https://huggingface.co/datasets/meetween/mumospee). ## Overview At this version it includes below languages and data soruces: ```python _LANGUAGES = ["en", "bg", "de", "ar", "fr"] _TAGS = ["CoVoST", "GigaSpeech", "PeopleSpeech", "Librispeech", "LibriTTS", "Emilia", "MOSEL"] ``` ## Data Sources The initial release includes metadata and download scripts for accessing the following publicly available datasets: - [CoVoST](https://github.com/facebookresearch/covost) - [GigaSpeech](https://github.com/SpeechColab/GigaSpeech) - [people-speech](https://mlcommons.org/datasets/peoples-speech/) - [LibriSpeech](https://www.openslr.org/12) - [LibriTTS](https://openslr.org/60/) - [Emilia](https://emilia-dataset.github.io/Emilia-Demo-Page/#dataset) - [MOSEL](https://huggingface.co/datasets/FBK-MT/mosel) ## Mumospee dataset structure Mumospee is available at [HuggingFace](https://huggingface.co/datasets/meetween/mumospee) without providing all the audio data directly, but the urls or scripts to access the datasets. In the metadata csv, each row is a sample representing the metadata of an audio, a video or a clip consisting of the following information: - "path": the relative path of the audio file to the sample. - "url": the link to download the parquet containing the audio, video or the clip of it. - "type": the sample is an audio or video. - "duration": the duration of the sample in second. - "language": the language of the video or audio. - "transcript": the transcript of the video or audio. - "tag": the origin of the sample. - "split": the sample is in split, test, or validation section in the original dataset. - "license": the license to use this sample. Here is an example sample: ```json { "path": "3660-172183-0000.flac", "url": "https://huggingface.co/datasets/meetween/mumospee_librispeech/resolve/main/librispeech-parquet/dev-other.parquet", "type": "audio", "duration": 5.405, "language": "en", "transcript": "GERAINT AS HE HAD BEEN USED TO DO WHEN HE WAS AT ARTHUR'S COURT FREQUENTED TOURNAMENTS", "tag": "Librispeech", "split": "validation", "license": "CC-BY-4.0" } ``` ## Example Usage ```python dataset= load_dataset("meetween/mumospee_small", trust_remote_code=True) print(dataset) # To get the first row of the dataset. sample_first = dataset["train"][0] ``` The defaul outputs all the samples from train split. To get another splits: ```python # To get the dataset from test or validation split dataset_test = load_dataset("meetween/mumospee_small", "test", trust_remote_code=True) dataset_validation = load_dataset("meetween/mumospee_small", "validation", trust_remote_code=True) ``` - ### Filters ### There are filters to select dataset samples from specific groups: ```python # To get the dataset of langauge "en". dataset= load_dataset("meetween/mumospee_small", "test", language="en", trust_remote_code=True) # To get the dataset from MOSEL. dataset= load_dataset("meetween/mumospee_small", "train", tag="MOSEL", trust_remote_code=True) # You can also add combination of language and tag: get English from CoVoST from test split. dataset= load_dataset("meetween/mumospee_small", "test", language="en", tag="CoVoST", trust_remote_code=True) ``` Note: keep in mind that if a filter combination (including split) results to no dataset, you may get an value error like below: ```python ValueError: Instruction "train" corresponds to no data! ``` Also, make sure the values are from `_LANGUAGES` and `_TAG`. - ### Download audios ### You can download the parquet files with the audios data by using the `download_audio` parameter (the default is `None`): ```python dataset= load_dataset("meetween/mumospee_small", "test", download_audio=True, language="en", trust_remote_code=True) ``` ## License The metadata and download scripts are publicly available under a CC0 license. While the metadata itself is open, users must comply with the licensing terms of each underlying dataset. ---