--- license: apache-2.0 --- # UK & Ireland Accent Classification Model This is a model to classify and identify the accent of a UK or Ireland speaker among one of the following accents: * Irish English * Midlands English * Northern English * Scottish English * Southern English * Welsh English The model implements transfer learning feature extraction using [Yamnet](https://tfhub.dev/google/yamnet/1) model in order to train a model. ## 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) - log_mel spectrogram representing the log-mel spectrogram of the entire audio frame We will use the embeddings, which are the features extracted from the audio samples, as the input to our dense model. ## Dense Model The dense model that we used consists of: - An input layer which is embedding output of the Yamnet model - 4 Dense hidden layers and 4 Dropout layers - An output dense layer ## Dataset The dataset used is the **[Open-source Multi-speaker Corpora of the English Accents in the British Isles](https://openslr.org/83/)** which consists of a total of **17,877 audio files**. ### Dataset Info @inproceedings{demirsahin-etal-2020-open, title = {{Open-source Multi-speaker Corpora of the English Accents in the British Isles}}, author = {Demirsahin, Isin and Kjartansson, Oddur and Gutkin, Alexander and Rivera, Clara}, booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference (LREC)}, month = may, year = {2020}, pages = {6532--6541}, address = {Marseille, France}, publisher = {European Language Resources Association (ELRA)}, url = {https://www.aclweb.org/anthology/2020.lrec-1.804},\n\ ISBN = {979-10-95546-34-4}, } # Demo A demo is available in HuggingFace Spaces ...