How does Amharic Speech To Text work?
- Automatic Speech Recognition (ASR). ASR uses algorithms to identify and process spoken words, converting them into text by analyzing sound waves and patterns.
- Machine Learning. Machine Learning models are trained on vast amounts of Amharic speech data to improve accuracy and adaptability in recognizing various accents and contexts.
- Natural Language Processing (NLP). NLP techniques facilitate understanding of context and semantics in spoken language, ensuring that the transcribed text makes sense in its intended use.
- Phonetic Analysis. Phonetic analysis breaks down spoken Amharic into its phonemes, allowing for more precise recognition and transcription of the language's unique sounds.