---
datasets:
- narad/ravdess
language:
- en
metrics:
- f1
- accuracy
- recall
- precision
pipeline_tag: audio-classification
---

# Emotion Recognition in English Using RAVDESS and Wav2Vec 2.0

<!-- Provide a quick summary of what the model is/does. -->

This model extracts emotions from audio recordings. It was trained on RAVDESS, a dataset containing English audio recordings. The model recognises six emotions: anger, disgust, fear, happiness, sadness and surprise.

The model recreates the work of this [Greek emotion extractor](https://huggingface.co/m3hrdadfi/wav2vec2-xlsr-greek-speech-emotion-recognition/blob/main/README.md) using a pre-trained [Wav2Vec2](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) model to process the data. 


## Model Details

### Model Description

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- **Adapter from:** [Emotion Recognition in Greek](https://huggingface.co/m3hrdadfi/wav2vec2-xlsr-greek-speech-emotion-recognition/blob/main/README.md)
- **Model type:** NN with CTC
- **Language(s) (NLP):** English
- **Finetuned from model [optional]:** [wav2vec2](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english)

### Model Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

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## Environmental Impact

- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]

### Compute Infrastructure
Used Google Colab for training.

#### Software

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## Citation [optional]

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**BibTeX:**

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**APA:**

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