17 Facts About Speech recognition

Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability.

Some speech recognition systems require "training" where an individual speaker reads text or isolated vocabulary into the system.

Google's first effort at speech recognition came in 2007 after hiring some researchers from Nuance.

Speech recognition can be thought of as a Markov model for many stochastic purposes.

Dynamic time warping is an approach that was historically used for speech recognition but has now largely been displaced by the more successful HMM-based approach.

Success of DNNs in large vocabulary speech recognition occurred in 2010 by industrial researchers, in collaboration with academic researchers, where large output layers of the DNN based on context dependent HMM states constructed by decision trees were adopted.

Front-end speech recognition is where the provider dictates into a speech-recognition engine, the recognized words are displayed as they are spoken, and the dictator is responsible for editing and signing off on the document.

Back-end or deferred speech recognition is where the provider dictates into a digital dictation system, the voice is routed through a speech-recognition machine and the recognized draft document is routed along with the original voice file to the editor, where the draft is edited and report finalized.

Speech recognition is used mostly as a part of a user interface, for creating predefined or custom speech commands.

Speech recognition can allow students with learning disabilities to become better writers.

Speech recognition is very useful for people who have difficulty using their hands, ranging from mild repetitive stress injuries to involve disabilities that preclude using conventional computer input devices.

Speech recognition is used in deaf telephony, such as voicemail to text, relay services, and captioned telephone.

Performance of speech recognition systems is usually evaluated in terms of accuracy and speed.

Speech recognition by machine is a very complex problem, however.

Speech recognition is distorted by a background noise and echoes, electrical characteristics.

Speech recognition can become a means of attack, theft, or accidental operation.

Speaker recognition uses the same features, most of the same front-end processing, and classification techniques as is done in speech recognition.