Scribd
Upload
81 views9 pages

Automatic Speech Recognition

This document discusses automatic speech recognition by outlining what it is, the main difficulties involved, and how it is currently approached. It explains that the task is to convert spoken language into text or other representations, but that there are challenges like variability in speech, distinguishing similar sounds, and interpreting context. The document also notes some advantages, like efficiency, but also disadvantages such as lack of accuracy, interference from accents and noise, and inability to use in some environments. It concludes that speech recognition may eventually allow computers to understand meaning rather than just words.

Uploaded by

Ashwani Singh
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PPT, PDF, TXT or read online on Scribd
81 views9 pages

Automatic Speech Recognition

This document discusses automatic speech recognition by outlining what it is, the main difficulties involved, and how it is currently approached. It explains that the task is to convert spoken language into text or other representations, but that there are challenges like variability in speech, distinguishing similar sounds, and interpreting context. The document also notes some advantages, like efficiency, but also disadvantages such as lack of accuracy, interference from accents and noise, and inability to use in some environments. It concludes that speech recognition may eventually allow computers to understand meaning rather than just words.

Uploaded by

Ashwani Singh
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PPT, PDF, TXT or read online on Scribd
You are on page 1/ 9

Automatic Speech

Recognition
Automatic speech recognition
• What is the task?
• What are the main difficulties?
• How is it approached?
• How good is it?
• How much better could it be?

2/14
What is the task?
• Getting a computer to understand spoken
language
• By “understand” we might mean
– React appropriately
– Convert the input speech into another
medium, e.g. text
• Several variables impinge on this (see
later)

3/14
How do humans do it?

• Articulation produces
• sound waves which
• the ear conveys to the brain
• for processing
4/14
How might computers do it?

Acoustic waveform Acoustic signal

• Digitization
• Acoustic analysis of the
Speech recognition
speech signal
• Linguistic interpretation
5/14
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 prosodic features
• Pragmatics
– Filtering of performance errors (disfluencies)
6/34
Advantages
• Work processes become more efficient.
• Saves a great deal of labour.
• Improves efficiency, leads to more structured
work.
• Aiding the Visually- and Hearing-Impaired.
• Enabling Hands Free Technology.

7/14
Disadvantages
• Lack of Accuracy and Misinterpretation
• Accents and Speech Recognition
• Background Noise Interference
• Misused with pre-recorded verbal message
• Initial training cost high and poor productivity
• Can’t be used in cubicle environment

8/14
Conclusion
At some point in future, speech recognition may become
speech understanding.
The statistical models that allow computers to decide what
a person just said may someday allow the to grasp the
meaning behind the words.
Although it is a huge leap in terms of computational power
and software sophistication, some researchers argue that
speech recognition development offers the most direct line
from the computers of today to true artificial intelligence.

9/14

You might also like