Self-learning end-to-end automatic speech recognition

A system for self-learning end to end automatic speech recognition (ASR), the system comprising:

• a memory;
• wherein the memory stores a language model, a noise database and an automatic speech recognition model;
• a processor;
• the processor configured to run:
• an application programming interface (API);
• a text extractor;
• a language model builder;
• a pronunciation model;
• a text to speech engine;
• and
• a mixer;
• and
• the processor configured to:
• receive client text documents via the API;
• and
• using the text extractor:
• determine out of vocabulary (OOV), words from the client text documents;
• extract sentences containing OOV words from the client text documents;
• use the extracted sentences to create an n-gram based language model using the language model builder;
• add the n-gram based language model to the language model stored in memory;
• process the extracted sentences using the pronunciation model to produce a phonetic sequence of the OOV words;
• generate a plurality of audio samples for each sentence using the text to speech engine;
• in response to generating the plurality of audio samples for each sentence using the text to speech engine:
• augment, using the mixer, the plurality of audio samples for each sentence generated using the text to speech engine with noise from the noise database;
• and
• fine tune the ASR model stored in memory using noise augmented audio samples.