Speech recognition converts spoken words into digital text using technologies like natural language processing (NLP). Major advancements have been made, achieving error rates comparable to humans, with Microsoft and Google reporting around 5% and 4.9% respectively. Applications include voice-activated assistants, automated customer service, and hands-free computing.

1. Speech Recognition
Prepended by :Huda Seyam

2. What is
• Speech recognition is the process of capturing
spoken words using a microphone or telephone and
converting them into a digitally stored set of words
• A subset of speech recognition is voice recognition,
which is the technology for identifying a person
based on their voice

3. History
• First known attempt at
speech recognition
• A toy from 1922
• Worked by analysing the
signal strength at 500Hz

4. • The most advanced version of currently developed ASR
technologies revolves around what is called
Natural Language Processing, or NLP in short.
This variant of ASR comes the closest to allowing real
conversation between people and machine intelligence and
though it still has a long way to go before reaching an apex
of development, we’re already seeing some remarkable
results in the form of intelligent smart phone interfaces like
the Siri program on the iPhone and other systems used in
business and advanced technology contexts.

5. Performance
The quality of a speech recognition
systems are assessed according to two
factors:
• its accuracy (error rate in converting
spoken words to digital data)
• speed (how well the software can
keep up with a human speaker).

6. Follow
• Today, developments in natural language
processing and neural network technology
have improved the speech and voice
technology, so much so that today it is
reportedly on par with humans.
• In 2017. For example, the word error rate
for Microsoft’s voice technology has been
recorded at 5.1 percent by the company,
while Google reports that it has reduced its
rate to 4.9 percent.

7. A Basic Primer
on How
Automatic
Speech
Recognition
Works

10. Applications
• speech to speech translation
• Dictation [google document]
• hands-free computing
• Robotics
• automated customer service, If you have
ever paid a bill over the phone using an
automated system
• Smart Speaker
Highlighting Amazon[Alexa]

12. The Tuning Test:
How ASR is made to “Learn”
from Humans

13. References
• https://www.techemergence.com/ai-for-
speech-recognition/
• https://usabilitygeek.com/automatic-
speech-recognition-asr-software-an-
introduction/
• https://www.streetdirectory.com/travel_gui
de/139545/technology/key_differences_bet
ween_speech_recognition_and_voice_recog
nition.html
• https://www.youtube.com/watch?v=q67z7P
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