The document discusses speech recognition (SR), including its history, components, types, applications, examples, and weaknesses. SR is the process of converting spoken words to text in real-time. Early systems in the 1950s could only recognize single voices saying digits, but later systems developed vocabulary recognition and could understand continuous speech. SR systems can benefit those with disabilities or assist in tasks like medical transcription. Current applications include controlling devices, call routing, and dictation into word processors. Examples given are Microsoft Speech Recognition and digital assistants like Siri and Google Now. Weaknesses include noise interference and difficulties with similar-sounding words.

1. Field: Computational linguistics
Topic :Speech Recognition
how SR came to be and how it
works? How beneficial is it for
students?
Presenter:
AMADOU ADAMOU AMINOU

2. Have you ever talked to your
computer or your phone? Where
it actually recognized what you
said and than did something as a
result??

3. Contents
• History
• Introduction
• Types of Speech Recognition
• Components of SR
• Applications
• Examples of SR
• Weakness and flaws
• Conclusion
• References

4. INTRODUCTION
WHAT IS SPEECH RECOGNISTION?
• Speech recognition is a process by which a
computer takes a speech signal (recorded
using a microphone) and converts it into
words in real-time.
• SR simply is the process of converting spoken
input to text.
PELLOM B. Sonic: The University of Colorado Continuous, Speech
Recognition System.2001

5. History
• The first speech recognition system was invented by Bell
laboratories in 1952 in US. It could understand only digits
spoken by a single voice. The system is called the “AUDREY”
system.
• Ten years late labs in the US, Japan, England developed
hardware dedicated to recognize spoken sounds.
• They now have large vocabularies and can recognize
continuous speech.
Eugene Weinstein - Speech Recognition p15, Prentice hall 1995

6. Why was SRS invented
• Individuals With Disabilities – Assists those who have visual
impairment, hand immobility, dyslexia, etc.
• Medical Transcription – Reduces delays to write out
medical transcriptions
• Dictation - Converts words to text in emails or other word
documents (also helpful for English Language Learners).
• Access Menu Commands – Opens files using voice commands.
Eugene Weinstein - Speech Recognition p40-50, Prentice hall 1995

7. Speech recognition system consists of:
• A microphone.
• A speech recognition software.
• A computer to take and interpret the speech.
• A good quality soundcard for input and output.
• A proper and good pronunciation.
BGROUV, B T. (1989) computational linguistics, London, Longman

8. Two types of SR..
• Speaker-dependent systems
– Require “training” to “teach” the individual System
– More robust
– But less convenient
– And obviously less portable
• Speaker-independent systems
– Language coverage is reduced to compensate need to be
flexible in phoneme identification
– Clever compromise is to learn on the fly
Eugene Weinstein - Speech Recognition p40-45, Prentice hall 1995

9. Components
• Audio input
• Grammar
• Speech Recognition Engine
• Acoustic Model
• Recognized text

10. What’s hard about that?
• Digitization
– Converting analogue signal into digital representation.
• Signal processing
– Separating speech from background noise.
• Phonetics
– Variability in human speech.
• Phonology
– Recognizing individual sound distinctions (similar phonemes.)
• Lexicology and syntax
– Disambiguating homophones.
– Features of continuous speech.
• Syntax and pragmatics
– Interpreting features.
– Filtering of performance errors (disfluencies).
Eugene Weinstein - Speech Recognition p15-67, Prentice hall 1995.

11. Potential uses in education
• Teaching students of foreign languages to
pronounce vocabulary correctly
• Enabling students who are physically
handicapped who cant use keyboard.
• Enabling student with textual interpretive
problems e.g. Dyslexia to enter text verbally.
• Restrictive access on high security computer,
where a keyboard may be used by hackers.
BGROUV, B T. (1989) computational linguistics, London, Longman

12. Applications of Speech Recognition
• Speech recognition applications include
 controlling any devices in your home (e.g. video),
 Call routing (e.g., "I would like to make a collect call"),
 Simple data entry (e.g., entering a credit card number),
 Preparation of structured documents (e.g., A radiology
report),
 Speech-to-text processing (e.g., word processors or emails)
 In aircraft cockpits (usually termed Direct Voice Input).
BGROUV, B T. (1989) computational linguistics, London: LONMAN

13. Example: Microsoft Speech
Recognition – Windows 7

14. SIRI & GOOGLE
Intelligent Personal Assistant
developed by Apple.
Google Now is an intelligent personal
assistant developed by Google.
Both use a combination of speaker- dependent and speaker-independent
SR systems

15. Weakness and Flaws
• Low signal-to-noise ratio: the program needs to
hear the words spoken distinctly.
• Intensive use of device power.
• Homonyms e.g. “there” and “their”, “be” and
“bee”
• Overlapping speech.
• No program is 100% perfect
• Problem of understanding dialects and accents
Example: see video
A practical Intro to the computer Analysis of Language, Geoff Barnbrook,
1996, Edinburgh University press.

16. Conclusion
• Revolutionize the way people conduct
business over the Web and ,differentiate
world-class e-businesses.
• VoiceXML ties speech recognition and
telephony together
• At some point in the future, speech
recognition may become speech
understanding.
• voice-enabled Web solutions TODAY!

17. References
• PELLOM, B., Sonic: The University of Colorado
Continuous Speech Recognition System, 2001
• BOGUREV, B T. (1989) computational linguistics,
London: LONGMAN
• Eugene Weinstein - Speech Recognition, Prentice
hall 1995
• http://www.tldp.org/HOWTO/Speech-
Recognition-
• A practical Intro to the computer Analysis of
Language, Geoff BRANKROOK, 1996, Edinburgh
University press.