Update README.md

Adjusted Model card

README.md

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 ## Model description
 
-More information needed
+This model classifies UK & Ireland accents using feature extraction from [Yamnet](https://tfhub.dev/google/yamnet/1).
 
-## Intended uses & limitations
+### Yamnet Model
+Yamnet is an audio event classifier trained on the AudioSet dataset to predict audio events from the AudioSet ontology. It is available on TensorFlow Hub.
+Yamnet accepts a 1-D tensor of audio samples with a sample rate of 16 kHz.   
+As output, the model returns a 3-tuple:   
+- Scores of shape `(N, 521)` representing the scores of the 521 classes.
+- Embeddings of shape `(N, 1024)`.
+- The log-mel spectrogram of the entire audio frame.
 
-More information needed
+We will use the embeddings, which are the features extracted from the audio samples, as the input to our dense model.  
+
+For more detailed information about Yamnet, please refer to its [TensorFlow Hub](https://tfhub.dev/google/yamnet/1) page.
+
+### Dense Model
+The dense model that we used consists of:
+- An input layer which is embedding output of the Yamnet classifier.
+- 4 dense hidden layers and 4 dropout layers.
+- An output dense layer.
 
 ## Training and evaluation data
 
-More information needed
+The dataset used is the
+[Crowdsourced high-quality UK and Ireland English Dialect speech data set](https://openslr.org/83/)
+which consists of a total of 17,877 high-quality audio wav files.
+
+This dataset includes over 31 hours of recording from 120 vounteers who self-identify as
+native speakers of Southern England, Midlands, Northern England, Wales, Scotland and Ireland.
+
+For more info, please refer to the above link or to the following paper:
+[Open-source Multi-speaker Corpora of the English Accents in the British Isles](https://aclanthology.org/2020.lrec-1.804.pdf)
+
 
 ## Training procedure