Editing Dragon Dictate (section)

==Key Innovations==

=== '''Commercialize Continuous Speech Recognition''' ===
Dragon Systems was one of the first companies to successfully commercialize speech recognition technology for personal computer users. They made it accessible to a broader audience beyond research and specialized industries. Before, Dragon Dictate uses discrete speech and is speaker-dependent, adapting to the speaker’s voice and language model with every word. In 1990, Dragon demonstrated a 5,000-word continuous speech system for PCs and introduced Dragon Dictate 30K, the first large-vocabulary, speech-to-text system for general-purpose dictation. It allowed control of a PC using voice commands only and found acceptance among the disabled. The system had limited appeal in the broader marketplace because it required users to pause between words. And late in 1993, the Bakers realized that improvements in desktop computers would soon allow continuous voice recognition. By July 1997, Dragon had launched Dragon NaturallySpeaking, a continuous speech & voice recognition program for general-purpose use with a vocabulary of 23,000 words. The package won rave reviews and numerous awards.

=== '''Improved Accuracy''' ===
The Dragon Dictate’ acoustic adaptability is based in a three-level phonology and a stochastic model of production:<ref>[https://doi.org/10.1177/002383099203500218 Mandel, M. A. (1992). A Commercial Large-Vocabulary Discrete Speech Recognition System: DragonDictate. Language and Speech, 35(1–2), 237–246.]  </ref>

==== Three-level Phonology ====
This three-level approach alIows Dragon Dictate to adapt quickly to the user’s own speech, approaching the reference speaker’s performance within a few thousand words.

* Phonemes: It comprises 24 consonants, three unstressable syllabic resonants, and 17 vowels, including diphthongs and syllabic /r/.

* Phonemes in context (PICs): the fundamental unit of Dragon phonology, a PIC represents an augmented triphone, comprising:
** the phoneme before the one being modeled, as context
** the phoneme being modeled
** the phoneme after the one being modeled, as context
** the degree of prepausal lengthening of each phoneme due to its position in the word.

* Phonetics elements(PELs): Most instances of English /s/ have a lot in common acoustically, and even a highly context-dependent consonant like /t/ can show significant constancy. We implement this similarity as a slice of a very coarse spectrogram, a steady state called a phonetic element, or PEL.

==== A stochastic model of production ====
It represents pronunciations as [[Hidden Markov Models]] that are built from the speech of a reference speaker according to three-level phonology, which in turn have been restructured into phonemes-in-context (PICs) and segments of PICs . 

Performance is also improved by use of digram language modeling. Experience with labeling has led to several observations on Germanic resonants and on polyphthongs.

==== Adaptation ====
When a person starts using Dragon Dictate it makes a model of his or her speech: a user model. Initially this is just a copy of its base model, which is derived from the reference speaker’s voice, but with every word spoken it adapts to the user’s pronunciation and usage.

For example, Initial recognition performance, which is significantly poorer when the user is of opposite sex to the reference speaker, is improved by adapting the models in advance to a speaker of the user’s own sex through preadaptation.

=== '''Accessibility''' ===
Dragon Systems recognised the potential of speech recognition technology in enhancing accessibility for individuals with disabilities. Their software provided a means for people with mobility or dexterity challenges to interact with computers and create content independently.

# Dragon Dictate, despite its learning curve and motivation requirements, has the potential to significantly benefit individuals dealing with profound dysarthria and substantial computer access challenges. According to the research findings, it proves to be a valuable tool with substantial utility, capable of enhancing computer access capabilities and facilitating communication for two individuals with cerebral palsy.<ref>[[doi:10.1080/17501229.2016.1165230|Satsuki Nakai, David Beavan, Eleanor Lawson, Grégory Leplâtre, James M. Scobbie & Jane Stuart-Smith (2018) Viewing speech in action: speech articulation videos in the public domain that demonstrate the sounds of the International Phonetic Alphabet (IPA), Innovation in Language Learning and Teaching, 12:3, 212-220]]</ref>
# Dragon can also help those people with learning difficulties like dyslexia or other conditions where they find it challenging to express their ideas in writing. And it can help students with mental health conditions or anxiety related problems for making their tasks easier to relieve their stress.<ref>[https://whatsnext.nuance.com/en-gb/home-business-productivity-en-gb/how-dragon-speech-recognition-helps-students-with-disabilities/ How Dragon speech recognition helps students with disabilities]</ref>
# Dragon Dictate introduced the concept of using voice commands to control a computer, open applications, navigate the web, and perform various tasks. This added a new dimension to hands-free computer interaction. Nuance<ref>[https://www.microsoft.com/en-us/industry/nuance Microsoft + Nuance]</ref>, the company behind Dragon Dictate, is a major player in healthcare technology, offering speech recognition and documentation solutions tailored for healthcare professionals. Their technology allows doctors, nurses, and other healthcare providers to transcribe medical dictation and interact with electronic health records using voice commands to improve efficiency and bring more comfortable experience.