Update README.md

README.md

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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("iwonachristop/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
+
+Bibtex
+
+### Contributions
+
+Thanks to [@iwonachristop](https://github.com/iwona-christop) for adding this dataset.