|
--- |
|
library_name: keras |
|
tags: |
|
- SpeakerRecognition |
|
- Fast Fourier Transform (FFT) |
|
- Convnet |
|
- speech-recordings |
|
- SpeechClassification |
|
--- |
|
|
|
## Model description |
|
This model helps to classify speakers from the frequency domain representation of speech recordings, obtained via Fast Fourier Transform (FFT). |
|
The model is created by a 1D convolutional network with residual connections for audio classification. |
|
|
|
This repo contains the model for the notebook [**Speaker Recognition**](https://keras.io/examples/audio/speaker_recognition_using_cnn/). |
|
|
|
Full credits go to [**Fadi Badine**](https://twitter.com/fadibadine) |
|
|
|
## Dataset Used |
|
This model uses a [**speaker recognition dataset**](https://www.kaggle.com/kongaevans/speaker-recognition-dataset) of Kaggle |
|
|
|
## Intended uses & limitations |
|
This should be run with `TensorFlow 2.3` or higher, or `tf-nightly`. |
|
Also, The noise samples in the dataset need to be resampled to a sampling rate of 16000 Hz before using for this model so, In order to do this, you will need to have installed `ffmpg`. |
|
|
|
## Training and evaluation data |
|
During dataset preparation, the speech samples & background noise samples were sorted and categorized into 2 folders - audio & noise, and then noise samples were resampled to 16000Hz & then the background noise was added to the speech samples to augment the data. After that, the FFT of these samples was given to the model for the training & evaluation part. |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
|
|
| name | learning_rate | decay | beta_1 | beta_2 | epsilon | amsgrad | training_precision | |
|
|----|-------------|-----|------|------|-------|-------|------------------| |
|
|Adam|0.0010000000474974513|0.0|0.8999999761581421|0.9990000128746033|1e-07|False|float32| |
|
|
|
## Training Metrics |
|
Model history needed |
|
## Model Plot |
|
|
|
<details> |
|
<summary>View Model Plot</summary> |
|
|
|
 |
|
|
|
</details> |
|
|
|
<center> |
|
Model By : <a href="https://github.com/robotjellyzone">Kavya Bisht</a> |
|
</center> |
