Language engineering

1. संगोष्ठी-पत्र
प्रश्न-पत्र 302: भाषा अभभयांत्रत्रकी (Language Engineering)
विषय : भाषा अभभयांत्रत्रकी का परिचय औि क्षेत्र
ननर्देशक
श्री पीयूष प्रताप भसंह
अभसस्टेंट प्रोफे सि
प्रौद्योगगकी अध्ययन के न्द्र
भाषा विद्यापीठ
प्रस्तुतकताा,
अभित कु िाि झा
एि॰आई॰एल॰ई॰
भाषा विद्यापीठ
िहात्िा गांधी अंतििाष्रीय हहन्द्र्दी विश्िविद्यालय, िधाा
िहािाष्र- 442205

2. भाषा अभभयाांत्रिकी(Language Engineering)
 Language Engineering is the application of knowledge
of language to the development of computer systems
which can recognise, understand, interpret, and
generate human language in all its forms.
 In practice, Language Engineering comprises a set of
techniques and language resources. The former are
implemented in computer software and the latter are a
repository of knowledge which can be accessed by
computer software.

3. भाषा अभभयाांत्रिकी(Language Engineering)
Engineering
Electronic Engineering
Computer Engineering
Software Engineering
Hardware Engineering
Language Related Software
Language Engineering

4. DFD of Language Engineering System

5. Area of Language Engineering
 Speaker Identification and Verification
 Speech Recognition
 Character and Document Image Recognition
 Natural Language Processing
 Speech Generation
 Language Translator
 Segmentation
 Question-Answering System
 Text-to-Speech and Speech-to-Text
 Word sense Disambiguation
 Information retrieval and Information Extraction

6. Speaker Identification and Verification
 A human voice is as unique to an individual as a
fingerprint.
Voice
Matching Voice with Data Sample
Speaker Name Data sample is not
present

7. Speech Recognition
 स्पीच recognition िें यह पहचाना जाता है क्या बोला जा
िहा है।
 स्पीकि recognition िें यह पहचाना जाता है कक कौन
बोल िहा है।
Speech Recognition
Speaker Dependent Speaker Independent

8. Character and Document Image Recognition
 recognition of printed images, referred to as Optical
Character Recognition (OCR)
 recognising handwriting, usually known as Intelligent
Character Recognition (ICR)

9. Natural Language Processing
 Natural Language Understanding
 Natural Language Generation
NLP = NLU + NLG

10. Speech Generation
 Template based Speech Generation :-
 Speech is generated from filled templates, by playing
'canned' recordings or concatenating units of speech
(phonemes, words) together. Speech generated has to
account for aspects such as intensity, duration and
stress in order to produce a continuous and natural
response.

11. Language Translator
Source Language
Target Language
Translation
Translator
Human Machine

12. Segmentation
 Word Segmentation
 Topic Segmentation
 Sentence Segmentation

13. Resources used in Language Engineering
 Lexicons
 Specialist Lexicons
 Grammars
 Corpora

14. lexicons
 A lexicon is a repository of words and knowledge about
those words.
 This knowledge may include details of -
1. Grammatical structure of each word (morphology)
2. Sound structure (phonology)
3. Meaning of the word in different textual contexts
 A useful lexicon may have hundreds of thousands of
entries.
 Lexicons are needed for every language of application.

15. Specialist Lexicons
 Proper names
 Terminology
 Word nets-A word net describes the relationships
between words; for example, synonyms, antonyms,
collective nouns, and so on. These can be invaluable in
such applications as information retrieval, translator
workbenches and intelligent office automation
facilities for authoring.

16. Grammar
 A grammar describes the structure of a language at
different levels: word (morphological grammar),
phrase, sentence, etc.
 A grammar can deal with structure both in terms of
surface (syntax) and meaning (semantics and
discourse).

17. Corpora
Corpus
Text Corpus Speech Corpus
Annotated
Corpus
Un-annotated
corpus