Speech recognition models can be used along with acoustic models, a pronunciation dictionary, and language models to transcribe domain-specific terms and rare words by providing hints and improving transcription accuracy of specific words which powers virtual assistants.
Using static signal processing, machine learning algorithms, neural networks, and other technologies, speaker can be identified by comparing their speech to models of known speakers using feature extraction, speaker modeling and matching so that the model matches the best input voice.
Various algorithms and computation techniques are used to recognize speech into text and improve its accuracy of transcription using statistical modeling systems with complex probability and mathematical functions to determine the most likely outcome. Customised speech recognition models can be used along with acoustic models, a pronunciation dictionary, and language models to transcribe domain-specific terms and rare words by providing hints and improving transcription accuracy of specific words which powers virtual assistants, facilitating automated closed captioning, and enabling digital dictation platforms.