---
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: filename
    dtype: string
  - name: turno_id
    dtype: int64
  - name: turno_time
    dtype: string
  - name: sentence
    dtype: string
  - name: sentence_fono
    dtype: string
  - name: sentence_fono_sin_marcas
    dtype: string
  - name: sentence_orto
    dtype: string
  - name: sentence_orto_sin_marcas
    dtype: string
  - name: Provincia
    dtype: string
  - name: Enclave
    dtype: string
  - name: Fecha
    dtype: string
  - name: Duración
    dtype: string
  - name: Informantes
    dtype: string
  splits:
  - name: train
    num_bytes: 4600923777.433
    num_examples: 53971
  - name: validation
    num_bytes: 503026194.46
    num_examples: 6689
  - name: test
    num_bytes: 486076659.954
    num_examples: 6726
  download_size: 4707509912
  dataset_size: 5590026631.847
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
task_categories:
- automatic-speech-recognition
- conversational
language:
- es
pretty_name: COSER-ASR Subset
size_categories:
- 10K<n<100K
---




# Introduction
The "COSER-ASR" Subset is a specialized extract from the "Corpus Oral y Sonoro del Español Rural" (COSER; Fernández-Ordóñez 2005-present), meaning the "Audible Corpus of Spoken Rural Spanish". This dataset has been specifically curated to facilitate the fine-tuning of Whisper, an automatic speech recognition system. For this purpose, audio and text segments ranging from 3 to 30 seconds have been automatically extracted from the COSER corpus. These segments provide concise and diverse samples of spoken rural Spanish, ideal for training and refining speech recognition models. To ensure manageability and efficient processing, a maximum of 1024 tokens were used in the dataset, striking a balance between comprehensive coverage and computational efficiency.
# Content and Demographic Focus
The original COSER dataset includes 218 transcriptions of semi-structured interviews primarily with elderly, less-educated individuals from rural Spain. These interviews, each averaging around 54 minutes, are rich in dialectal variations and linguistic nuances, offering valuable insights into traditional Spanish dialects.

# Transcription Approach
The "coser" dataset provides multiple layers of transcription to cater to different linguistic and computational needs:

### Original Transcription (sentence): 
This is the direct transcription of the audio segments, preserving the original speech as closely as possible and the complete original transcription.

### Phonological Approximation (sentence_fono): 
Here, the transcription is modified to reflect the phonological characteristics of the dialectal pronunciation. This version is crucial for understanding the phonetic nuances of rural Spanish dialects.

### Phonological Transcription without Discourse Markers (sentence_fono_sin_marcas): 
This transcription removes discourse markers such as laughter, assent, etc., that are typically enclosed in square brackets. It offers a cleaner version focusing solely on the spoken words.

### Orthographic Correspondence (sentence_orto): 
This layer provides the standard orthographic equivalent of the words transcribed phonologically. It bridges the gap between dialectal speech and standard Spanish orthography.

### Orthographic Transcription without Discourse Markers (sentence_orto_sin_marcas): 
Similar to the phonological version without markers, this transcription provides a standard orthographic text devoid of any discourse markers. This is particularly useful for applications requiring clean text data.

# Limitations

Limitations of this model include the fact that the time intervals in the COSER corpus are not systematically aligned, meaning that there may not be a perfect one-to-one correspondence between the audio and text data.
# Additional Information and Resources
To explore more about the COSER corpus, its methodologies, and the full range of transcriptions, visit http://coser.lllf.uam.es/ and http://coser.lllf.uam.es/transcripcion.php. These resources provide an in-depth look at the COSER project, detailing its comprehensive approach to capturing the linguistic diversity of rural Spanish.

# References

Fernández-Ordóñez, I. (Ed.). (2005-present). Corpus Oral y Sonoro del Español Rural. Retrieved April 15, 2022, from http://www.corpusrural.es/