Dataset Card for Modified SHEMO

Dataset Summary

This dataset is a corrected and modified version of the Sharif Emotional Speech Database (ShEMO) named modified_shemo. The original dataset contained significant mismatches between audio files and their corresponding transcriptions. This version resolves those issues, resulting in a cleaner and more reliable resource for Persian Speech Emotion Recognition (SER) and Automatic Speech Recognition (ASR).

Curation and Correction

The original ShEMO dataset suffered from incorrectly named transcription files, leading to a high baseline Word Error Rate (WER). We addressed this by:

Using an ASR system with a 4-gram language model to identify and re-align mismatched audio-text pairs.
Correcting 347 files that had high error rates.

This modification process significantly improved the dataset's quality, reducing the overall WER from 51.97% to 30.79%. More details are available at this GitHub repository and in this paper.

Dataset Statistics

Below are the detailed statistics for this dataset, calculated using an analysis script.

Emotion Distribution

==================================================
           Emotion Distribution
==================================================
   Emotion  Percentage (%)
   neutral           38.66
     happy           06.76
       sad           12.03
     angry           34.73
  surprise           06.73
      fear           01.06
--------------------------------------------------

Overall Statistics

============================================================
        Overall Statistics for Modified SHEMO Dataset
============================================================
📊 Total Number of Files: 3000
⏰ Total Dataset Duration: 3.43 hours
🗣️ Total Number of Speakers: 87
------------------------------------------------------------

Gender-Emotion Breakdown

==================================================
           Gender-Emotion Breakdown
==================================================
gender     female  male
emotion                
anger         449   593
fear           20    12
happiness     113    90
neutral       346   814
sadness       224   137
surprise      111    91
--------------------------------------------------

Supported Tasks

Speech Emotion Recognition: The dataset is ideal for training models to recognize various emotions from speech. The emotion column is used for this task.
Automatic Speech Recognition: With precise transcriptions available in the transcript column, the dataset can be used to train ASR models for the Persian language.

Languages

The primary language of this dataset is Persian (Farsi).

Dataset Structure

Data Instances

An example from the dataset looks as follows:

{
  "audio": {
    "path": "/path/to/F21N05.wav",
    "array": ...,
    "sampling_rate": 16000
  },
  "speaker_id": "F21",
  "gender": "female",
  "emotion": "neutral",
  "transcript": "مگه من به تو نگفته بودم که باید راجع به دورانت سکوت کنی؟",
  "ipa": "mæge mæn be to nægofte budæm ke bɑyæd rɑdʒeʔ be dorɑnt sokut koni"
}

Data Fields

audio: A dictionary containing the audio file's array and its sampling rate (set to 16kHz in this dataset).
speaker_id: A unique identifier for each speaker (e.g., F01 or M23).
gender: The gender of the speaker (female or male).
emotion: The emotion label for each audio file (angry, fear, happy, sad, surprise, neutral).
transcript: The precise orthographic transcription of the utterance in Persian.
ipa: The phonetic transcription of the utterance according to the IPA standard.

Data Splits

The dataset does not have predefined train, validation, and test splits by default. Users can easily create their own splits using the .train_test_split() method from the datasets library.

How to Use

To load the dataset, use the datasets library:

from datasets import load_dataset

dataset = load_dataset("aliyzd95/modified_shemo")

print(dataset["train"][0])

Additional Information

Citation Information

If you use this dataset in your research, please cite the original paper:

@misc{https://doi.org/10.48550/arxiv.2211.09956,
  doi = {10.48550/ARXIV.2211.09956},
  url = {https://arxiv.org/abs/2211.09956},
  author = {Yazdani, Ali and Shekofteh, Yasser},
  keywords = {Audio and Speech Processing (eess.AS), Artificial Intelligence (cs.AI), Sound (cs.SD), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Computer and information sciences, FOS: Computer and information sciences, I.2, 68T10 (Primary) 68T50, 68T07 (Secondary)},
  title = {A Persian ASR-based SER: Modification of Sharif Emotional Speech Database and Investigation of Persian Text Corpora},
  publisher = {arXiv},
  year = {2022},
  copyright = {arXiv.org perpetual, non-exclusive license}
}

Datasets:

aliyzd95
/

modified_shemo

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