readme: ---
  language: "en"
  thumbnail:
  tags:
  - audio-classification
  - speechbrain
  - Emotion
  - Recognition
  - wav2vec2
  - pytorch
  license: "apache-2.0"
  datasets:
  - iemocap
  metrics:
  - Accuracy
  ---
  
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  # Emotion Recognition with wav2vec2 base on IEMOCAP
  
  This repository provides all the necessary tools to perform emotion recognition with a fine-tuned wav2vec2 (base) model using SpeechBrain. 
  It is trained on IEMOCAP training data.
  
  
  For a better experience, we encourage you to learn more about
  [SpeechBrain](https://speechbrain.github.io). The model performance on IEMOCAP test set is:
  
  | Release | Accuracy(%) | 
  |:-------------:|:--------------:|
  | 19-10-21 | 78.7 (Avg: 75.3) | 
  
  
  ## Pipeline description
  
  This system is composed of an wav2vec2 model. It is a combination of convolutional and residual blocks. The embeddings are extracted using attentive statistical pooling. The system is trained with Additive Margin Softmax Loss.  Speaker Verification is performed using cosine distance between speaker embeddings.
  
  The system is trained with recordings sampled at 16kHz (single channel).
  The code will automatically normalize your audio (i.e., resampling + mono channel selection) when calling *classify_file* if needed.
  
  
  ## Install SpeechBrain
  
  First of all, please install the **development** version of SpeechBrain with the following command:
  
  ```
  pip install speechbrain
  ```
  
  Please notice that we encourage you to read our tutorials and learn more about
  [SpeechBrain](https://speechbrain.github.io).
  
  ### Perform Emotion recognition
  
  An external `py_module_file=custom.py` is used as an external Predictor class into this HF repos. We use `foreign_class` function from `speechbrain.pretrained.interfaces` that allow you to load you custom model. 
  
  ```python
  from speechbrain.pretrained.interfaces import foreign_class
  classifier = foreign_class(source="speechbrain/emotion-recognition-wav2vec2-IEMOCAP", pymodule_file="custom_interface.py", classname="CustomEncoderWav2vec2Classifier")
  out_prob, score, index, text_lab = classifier.classify_file("speechbrain/emotion-recognition-wav2vec2-IEMOCAP/anger.wav")
  print(text_lab)
  ```
   The prediction tensor will contain a tuple of (embedding, id_class, label_name).
  
  ### Inference on GPU
  To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.
  
  ### Training
  The model was trained with SpeechBrain (aa018540).
  To train it from scratch follows these steps:
  1. Clone SpeechBrain:
  ```bash
  git clone https://github.com/speechbrain/speechbrain/
  ```
  2. Install it:
  ```
  cd speechbrain
  pip install -r requirements.txt
  pip install -e .
  ```
  
  3. Run Training:
  ```
  cd  recipes/IEMOCAP/emotion_recognition
  python train_with_wav2vec2.py hparams/train_with_wav2vec2.yaml --data_folder=your_data_folder
  ```
  
  You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/15dKQetLuAhSyg4sNOtbSDnuxFdEeU4zQ?usp=sharing).
  
  ### Limitations
  The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
  
  # **Citing SpeechBrain**
  Please, cite SpeechBrain if you use it for your research or business.
  
  ```bibtex
  @misc{speechbrain,
    title={{SpeechBrain}: A General-Purpose Speech Toolkit},
    author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
    year={2021},
    eprint={2106.04624},
    archivePrefix={arXiv},
    primaryClass={eess.AS},
    note={arXiv:2106.04624}
  }
  ```
  
  # **About SpeechBrain**
  - Website: https://speechbrain.github.io/
  - Code: https://github.com/speechbrain/speechbrain/
  - HuggingFace: https://huggingface.co/speechbrain/
  