MGASALUCAS/ASR_Notebook.

objective her is to develop a machine learning ASR model capable of accurately recognizing spoken words in Swahili. # ASR_Notebook. The Objective here is to develop a machine learning ASR model capable of accurately recognizing spoken words in Swahili. # Dataset. I have 4 files. - test.csv - This is the dataset that will be used for model testing. - train.csv - Train contains the target. This is the dataset that that will be used to train the model. - test_audios.zip - Test audios that will be used to test the model. - train_audios.zip - Train the audios that will be used to train the model. ### Step 1: To start with the problem , I look on data. CSV files and Audio Data. I converted mp3 audio data to wav file format. I thought this being compactible and best format with Machine Learning Algorithm for this. ### Step 2: After uploading csv files we convert them into intergers , then encoding and decoding functions were defined , data were splitted into training and validation. ### Step 3: This step we define CTC Loss function , model function after that decoding of test data were defined. ### Step 4: Model training and after that we check the result using our validation data. # Progress With the notebook given here in the table, I have built the pipeline. But when I finally trained the model, I got no predictions.