How does Tajik Speech To Text work?
- Deep Learning. Deep learning models, such as recurrent neural networks (RNNs), are trained on large datasets of spoken Tajik to accurately predict text output from audio input.
- Language Models. Language models are employed to predict the probability of sequences of words, improving the system’s ability to generate coherent and contextually relevant transcriptions.
- Feature Extraction. This technique involves analyzing the audio signal to extract significant features, which helps the model understand key phonetic elements of the Tajik language.
- Acoustic Modeling. Acoustic models represent the relationship between phonemes and their potential corresponding audio signals, crucial for accurate speech recognition in Tajik.
