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---
pretty_name: nEMO
language:
- pl
license: cc-by-nc-sa-4.0
multilinguality: monolingual
size_categories:
- 1K<n<10K
task_categories:
- audio-classification
- automatic-speech-recognition
- text-to-speech
task_ids:
- audio-emotion-recognition
- audio-language-identification
- sentiment-analysis
- speaker-identification
dataset_info:
features:
- name: audio
dtype: audio
- name: emotion
dtype: string
- name: raw_text
dtype: string
- name: normalized_text
dtype: string
- name: speaker_id
dtype: string
- name: gender
dtype: string
- name: age
dtype: string
splits:
- name: train
num_bytes: 531732105.875
num_examples: 4481
download_size: 531171916
dataset_size: 531732105.875
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# nEMO: Dataset of Emotional Speech in Polish
## Dataset Description
nEMO is a simulated dataset of emotional speech in the Polish language. The corpus contains over 3 hours of samples recorded with the participation of nine actors portraying six emotional states: anger, fear, happiness, sadness, surprise, and a neutral state. The text material used was carefully selected to represent the phonetics of the Polish language. The corpus is available for free under the Creative Commons license (CC BY-NC-SA 4.0).
### Example Usage
The nEMO dataset can be loaded and processed using the datasets library:
```python
from datasets import load_dataset
nemo = load_dataset("amu-cai/nEMO", split="train")
```
### Supported Tasks
- `audio-classification`: This dataset was mainly created for the task of speech emotion recognition. Each recording is labeled with one of six emotional states (anger, fear, happiness, sadness, surprised, and neutral). Additionally, each sample is labeled with speaker id and speaker gender. Because of that, the dataset can also be used for different audio classification tasks.
- `automatic-speech-recognition`: The dataset includes orthographic and normalized transcriptions for each audio recording, making it a useful resource for automatic speech recognition (ASR) tasks. The sentences were carefully selected to cover a wide range of phonemes in the Polish language.
- `text-to-speech`: The dataset contains emotional audio recordings with transcriptions, which can be valuable for developing TTS systems that produce emotionally expressive speech.
### Languages
nEMO contains audio and transcription in Polish language.
## Dataset Structure
### Data Instances
```python
{
'audio': {
'path': None,
'array': array([ 6.10351562e-05, -3.05175781e-05, -3.05175781e-05, ...,
6.10351562e-05, -1.22070312e-04, 1.83105469e-04]),
'sampling_rate': 24000
},
'emotion': 'surprised',
'raw_text': 'Ucho wykrywa dźwięki o różnej częstotliwości.',
'normalized_text': 'ucho wykrywa dźwięki o różnej częstotliwości',
'speaker_id': 'WR0',
'gender': 'male',
'age': '23'
}
```
### Data Fields
- `audio` (audio) - dictionary containing audio array, path and sampling rate,
- `emotion` (string) - label corresponding to emotional state,
- `raw_text` (string) - original (orthographic) transcription of the audio,
- `normalized_text` (string) - normalized transcription of the audio,
- `speaker_id` (string) - id of speaker,
- `gender` (string) - gender of the speaker,
- `age` (string) - age of the speaker.
### Data Splits
The nEMO dataset is provided as a whole, without predefined training and test splits. This allows researchers and developers flexibility in creating their splits based on the specific needs.
## Additional Information
### Licensing Information
The dataset is available under the Creative Commons license (CC BY-NC-SA 4.0).
### Citation Information
You can access the nEMO paper at [link]. Please cite the paper when referencing the nEMO dataset as:
```
@article{}
```
### Contributions
Thanks to [@iwonachristop](https://github.com/iwona-christop) for adding this dataset. |