metadata

license: cc-by-nc-nd-4.0
dataset_info:
  config_name: tedx_spanish
  features:
    - name: audio_id
      dtype: string
    - name: audio
      dtype:
        audio:
          sampling_rate: 16000
    - name: speaker_id
      dtype: string
    - name: gender
      dtype: string
    - name: duration
      dtype: float32
    - name: normalized_text
      dtype: string
  splits:
    - name: train
      num_bytes: 1597201769.901
      num_examples: 11243
  download_size: 1610347743
  dataset_size: 1597201769.901
configs:
  - config_name: tedx_spanish
    data_files:
      - split: train
        path: tedx_spanish/train-*
    default: true
language:
  - es
tags:
  - tedx talks
  - spontaneous spanish
  - ciempiess project
  - ciempiess-unam project
pretty_name: TEDX SPANISH CORPUS
size_categories:
  - 10K<n<100K
task_categories:
  - automatic-speech-recognition

Dataset Card for tedx_spanish

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: CIEMPIESS-UNAM Project
Repository: TEDX SPANISH at OpenSLR
Point of Contact: Carlos Mena

Dataset Summary

According to the TEDx website:

In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized (subject to certain rules and regulations).

Therefore, the TEDX SPANISH CORPUS is a dataset created from TEDx talks in Spanish and it aims to be used in the Automatic Speech Recognition (ASR) Task.

The TEDX SPANISH CORPUS is a gender unbalanced corpus of 24 hours of duration. It contains spontaneous speech of several expositors in TEDx events; most of them are men.

Example Usage

The TEDX SPANISH CORPUS contains only the train split:

from datasets import load_dataset
tedx_spanish = load_dataset("ciempiess/tedx_spanish")

It is also valid to do:

from datasets import load_dataset
tedx_spanish = load_dataset("ciempiess/tedx_spanish",split="train")

Supported Tasks

automatic-speech-recognition: The dataset can be used to test a model for Automatic Speech Recognition (ASR). The model is presented with an audio file and asked to transcribe the audio file to written text. The most common evaluation metric is the word error rate (WER).

Languages

The language of the corpus is Spanish.

Dataset Structure

Data Instances

{
  'audio_id': 'TEDX_F_003_SPA_0009', 
  'audio': {'path': '/home/carlos/.cache/HuggingFace/datasets/downloads/extracted/3025147eaa2bb2c143e0a8a1842f1f7cd0cacf157626ed4098de35ce4f7976d4/train/female/F_003/TEDX_F_003_SPA_0009.flac', 
  'array': array([ 2.6855469e-03,  2.5329590e-03,  2.0141602e-03, ...,
        9.1552734e-05, -5.7983398e-04,  1.6479492e-03], dtype=float32), 'sampling_rate': 16000
  }, 
  'speaker_id': 'F_003', 
  'gender': 'female', 
  'duration': 5.658999919891357, 
  'normalized_text': 'a estos espacios desde abril trece tuvimos dieciocho espacios que presentaron un proyecto inédito'
}

Data Fields

audio_id (string) - id of audio segment
audio (datasets.Audio) - a dictionary containing the path to the audio, the decoded audio array, and the sampling rate. In non-streaming mode (default), the path points to the locally extracted audio. In streaming mode, the path is the relative path of an audio inside its archive (as files are not downloaded and extracted locally).
speaker_id (string) - id of speaker
gender (string) - gender of speaker (male or female)
duration (float32) - duration of the audio file in seconds.
normalized_text (string) - normalized audio segment transcription

Data Splits

The corpus counts just with the train split which has a total of 11243 speech files from 40 female speakers and 102 male speakers with a total duration of 24 hours and 29 minutes.

Dataset Creation

Curation Rationale

The TEDX SPANISH CORPUS (TSC) has the following characteristics:

The TSC has an exact duration of 24 hours and 29 minutes. It has 11243 audio files.
The TSC counts with 142 different speakers: 102 men and 40 women.
Every audio file in the TSC has a duration between 3 and 10 seconds approximately.
Data in TSC is classified by speaker. It means, all the recordings of one single speaker are stored in one single directory.
Data is also classified according to the gender (male/female) of the speakers.
Audio and transcriptions in the TSC are segmented and transcribed by native speakers of the Spanish language
Audio files in the TSC are distributed in a 16khz@16bit mono format.
Every audio file has an ID that is compatible with ASR engines such as Kaldi and CMU-Sphinx.

Source Data

Initial Data Collection and Normalization

The TEDX SPANISH CORPUS is a speech Corpus designed to train acoustic models of automatic speech recognition and it is made out of recordings of from TEDx talks in Spanish.

Annotations

Annotation process

The annotation process is at follows:

1. A whole podcast is manually segmented keeping just the portions containing good quality speech.
1. A second pass os segmentation is performed; this time to separate speakers and put them in different folders.
1. The resulting speech files between 5 and 10 seconds are transcribed by students from different departments (computing, engineering, linguistics). Most of them are native speakers but not with a particular training as transcribers.

Who are the annotators?

The TEDX SPANISH CORPUS was created under the umbrella of the social service program "Desarrollo de Tecnologías del Habla" of the "Facultad de Ingeniería" (FI) in the "Universidad Nacional Autónoma de México" (UNAM) between 2016 and 2019 by Carlos Daniel Hernández Mena, head of the program.

Personal and Sensitive Information

The dataset could contain names revealing the identity of some speakers; on the other side, the recordings come from publicly available podcasts, so, there is not a real intent of the participants to be anonymized. Anyway, you agree to not attempt to determine the identity of speakers in this dataset.

Considerations for Using the Data

Social Impact of Dataset

This dataset is valuable because it contains spontaneous speech.

Discussion of Biases

The dataset is not gender balanced. It is comprised of 40 female and 102 male speakers.

Other Known Limitations

"TEDX SPANISH CORPUS" by Carlos Daniel Hernández Mena is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC-BY-NC-ND-4.0)[https://creativecommons.org/licenses/by-nc-nd/4.0/] and it utilizes materials shared by TEDX-Talks. This work was created with the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

Dataset Curators

The dataset was collected by students belonging to the social service program "Desarrollo de Tecnologías del Habla". It was curated by Carlos Daniel Hernández Mena in 2019.

Licensing Information

CC-BY-NC-ND-4.0

Citation Information

@misc{carlosmena2019tedxspanish,
      title={TEDX SPANISH CORPUS: Audio and Transcriptions taken from TEDx Talks.}, 
      author={Hernandez Mena, Carlos Daniel},
      organization={CIEMPIESS-UNAM Project},
      year={2019},
      url={https://huggingface.co/datasets/ciempiess/tedx_spanish},
}

Contributions

The author would like to thank to Alejandro V. Mena, Elena Vera and Angélica Gutiérrez for their support to the social service program: "Desarrollo de Tecnologías del Habla." He also thanks to the social service students for all the hard work.

Special thanks to the TEDx Team team for publishing all the recordings that constitute the TEDX SPANISH CORPUS.

This dataset card was created as part of the objectives of the 16th edition of the Severo Ochoa Mobility Program (PN039300 - Severo Ochoa 2021 - E&T).

Datasets:

ciempiess
/

tedx_spanish