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Future Trends in Computing Dr. Manish R. Joshi.

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1 Future Trends in Computing Dr. Manish R. Joshi

2 Image Recognition ? Future Trends in Computing

3 Understanding Expressions ? Future Trends in Computing

4 Language Processing Previous month only Sameer’s two hands became four. British ruled India poetically God is as per rate Translation

5 Decision Making ? How many minutes are with the captain to take a decision Future Trends in Computing Unstructured Decisions How many seconds are with you to take a decision To whom handle the last over – All of a sudden you saw a bike racing towards you –

6 Innovation Future Trends in Computing

7 Vision Image Recognition Intelligence Language Processing Expression Understanding – Emotion Modeling Learning from past Experience Decision Making Unstructured Decisions Innovation Poem Creation Art Speech Future Trends in Computing

8 Vision : Image Recognition It takes few mili seconds (ms) to recognize your mother from the crowd of 100 women It is still not possible to search image in true sense What search engines search for you are tagged images. Automatic image tagging is one of the major research areas Future Trends in Computing

9 1. Image/Video Coding and Transmission Still image and video coding, video streaming, coding standards 2. Image/Video Processing and Analysis Image filtering, biometrics restoration, computer vision 3. Image Formation Biomedical imaging, remote sensing imaging, optical imaging 4. Image Scanning, Printing, Display and Color Scanning and sampling, image rendering, image quality assessment 5. Image/Video Storage, Retrieval and Authentication Image/video databases, video indexing, content-based multimedia 6. Applications Application of image processing technology to any field, including biomedical sciences, astronomy, geosciences, environment, etc. Future Trends in Computing Research Topics in Image Processing Topics list from 2010 ICIP CFP

10 Future Trends in Computing Research Topics in Digital Image Processing Image acquisition Medical image processing Pattern recognition and analysis Visualization Image coding and compression Face Recognition Super-resolution imaging Image segmentation Radar Image Processing Sonar Image Processing Digital Signal Processing Mobile Signal Processing Motion Detection Watermarking Detection Content-based Image retrieval Video Signal Processing Multi-channel Filtering Signal Noise Control Signal Processing (Fuzzy) Signal Processing (Neural Network) Topics List from 2011 ICDIP CFP

11 Expression Modeling Can computer be trained to understand human expressions Future Trends in Computing Image Recognition is possible – but is it possible to understand the mood. Human being can understand expressions by Face reading Gesture / Posture – Body Language Way of Speech Research

12 Language Processing The process of developing a computer system that understand language completely is difficult. Scientist agree that true Machine Translation is impossible and shifted the focus towards Human Aided Machine Translation. But it is an interesting fact that 90 % of sentences uttered by average 3 year child are correct. Future Trends in Computing

13 Research Topics in Computational Linguistics Syntax, semantics, grammar, and the lexicon, Summarization, Lexical semantics and ontologies, Language generation, Paraphrasing and textual entailment, Parsing and chunking, Word segmentation, and tagging, Dialogue and conversational agents, Phonology/morphology Computational pragmatics, Computational models of discourse Spoken language processing, understanding and speech-to- speech translation psychological and mathematical models of language

14 Information retrieval, Question answering, Word sense disambiguation, Information extraction and text mining Semantic role labeling, Sentiment analysis and opinion mining Corpus-based modeling of language, Multilingual Machine translation and translation aids, Corpus development and language resources Future Trends in Computing Research Topics in Computational Linguistics Topics List from 2010 CoLing CFP

15 Decision Making Computers are good at taking structured Decisions Deciding DA based on Payscales Allotting reservation if seats are available Allow withdrawal of money if password is correct Playing Chess Future Trends in Computing Computer can only assist in unstructured Decision Making Whether certain team should bat first or field first after winning toss Forming the Cabinet of Ministers

16 Knowledge Discovery and Data Mining Clustering – Creating clusters of customers who spend more than 10,000 Rs. Per year on cosmetics. Classification – Determining whether a particular employee shall purchase a new car under a certain scheme. Spam Mails Association Rules Mining – Identifying items that are purchased together. Learning from past data: Mining useful information from the data Computers are programmed to find out useful patterns, association rules etc. Future Trends in Computing Development of Recommender Systems.

17 Future Trends in Computing Research Topics in KDD Topics List from 2010 ECDM CFP Applications Databases Bioinformatics Biometrics Image analysis Financial modeling Forecasting Classification Clustering Social Networks Core Data Mining Topics Parallel and distributed data mining algorithms Data streams mining Graph mining Spatial data mining Text, video, multimedia data mining Web mining Pre-processing techniques Visualization Security and information hiding in data mining

18 Innovation Imagination Creativity Intuition Computer can be programmed to mimic the way certain poet write poems Several Application are available which write poem by just putting words together in some manner to make some sense. Even computers are programmed to draw their own designs Future Trends in Computing

19 Other Areas Include Languages and compilers for HPC Parallel and distributed system architectures Parallel and distributed software technologies Parallel and distributed algorithms, Grid and cluster computing Web services and internet computing Performance evaluation and measurement Tools and environments for s/w development Distributed systems and applications High-performance scientific and engineering computing Biological/molecular computing Collaborative and cooperative environments Mobile computing and wireless communications Embedded systems, Peer-to-peer computing

20 Pervasive/ubiquitous computing and intelligence Autonomic, reliability and fault-tolerance Trust, security and privacy Computing Ethics Dependable Computing and Systems Web-based Computing and Service-Oriented Architecture Peta Scale Computing Cloud Computing Cryptography, Data communication, Operations Research Data Encryption, Security, Spam Detection, Software Engineering, Distributed OS, OPEN Source Future Trends in Computing Other Areas Include

21 Thank You !!!

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23 Process of Learning Language by Babies Dr. Manish Joshi

24 Child Language Acquisition The process of developing a computer system that understand language completely is difficult. Scientist agree that true Machine Translation is impossible and shifted the focus towards Human Aided Machine Translation. But it is an interesting fact that 90 % of sentences uttered by average 3 year child are correct. What thousand numbers of researchers can not achieve in decades, that a brain of three year’s child achieves --- HOW ? CAN WE MIMIC IT TO MAKE A COMPUTER SYSTEM LEARN LANGUAGE ? ? ?

25 Baby - AgeWhat they Can do ? New Born Babies Prefer their mothers voice than father or any other woman. Respond more positively to recording of their mothers native language as compared to any other language. Child Language Acquisition

26 Baby - AgeWhat they Can do ? Infants Respond to the cadence, rhythm and pitch of their mothers speech. Not yet developed the ability to identify the words from the speech Child Language Acquisition

27 Baby - AgeWhat they Can do ? 4 Months baby Starts perceiving entire range of phonemes - every phoneme uttered in language. Baby has the capacity to sense every phoneme from whatever language as diverse as Hindi and Malayalam. Babies Neurons will forge 100 Trillion connections, 20 times more than from birth. Child Language Acquisition

28 Baby - AgeWhat they Can do ? 8 Months baby Learns to find out individual words from non-stop stream of sound that makeup ordinary speech. Starts memorizing words just by listening. Even they can memorize words in a foreign language just by listening to somebody talk on the telephone. They don’t have the concept of word meaning Child Language Acquisition

29 Baby - AgeWhat they Can do ? 9 Months baby A part of brain used to store and index many kinds of memory becomes fully functional Babies start attaching meanings to words. Child Language Acquisition

30 Baby - AgeWhat they Can do ? 10 Months baby Begin to focus on distinction among phonemes of their native language and to ignore the differences among foreign sounds. Starts noticing grammatical morphemes. It allows them to learn more quickly the syllable and words of their native language. Child Language Acquisition

31 Baby - AgeWhat they Can do ? 15 Months baby Development process of brain for ‘Fast Mapping’ - Brain processes speech with phenomenal speed. A child needs more than a second to recognize even a familiar word ‘bay-by’ Child Language Acquisition

32 Baby - AgeWhat they Can do ? 18 Months baby Can recognize Ungrammatical sentence. Somehow learns the rule of grammar. Like - any verb ending in - ing must be preceded by the verb of to-be form Can utter few dozen of words, and can string together two word sentences occasionally. Child Language Acquisition

33 Baby - AgeWhat they Can do ? 24 Months baby Fast Mapping - Baby now takes only 600ms to understand ‘baby’ after hearing the syllable ‘bay’. Understands significance of grammatical morphemes before they actually use it. Child Language Acquisition

34 Baby - AgeWhat they Can do ? 36 Months baby 90 % of sentences uttered by average 3 year child are grammatically correct. Child Language Acquisition

35 Contribution of Computer Science : Artificial Neural Network Tries to mimic the way brain works. Applications : Can be used for simple classification. Use of statistical methods Tries to find the statistical regularities among the words along with use of some probabilistic models and use this knowledge for word sense disambiguation or for tagging the words. Child Language Acquisition As a baby learns by identifying statistical regularities among the speech, these methods tries to use the example base and use this statistical knowledge to predict about the input word.

36 Child Language Acquisition Lot of work for English language is in progress. We started our work to track how child acquires Marathi Language. Applications  We can standardize the process of learning Marathi Language as an additional language.  This study shall be helpful in the process of developing natural language applications that deals with Marathi Language.  This study can be helpful to increase the word dictionary of toddlers.  It can be helpful to understand the class of problem known as Disorders of Language Learning (Aphasia)

37 if we follow what child brain does we can reach to the target … some what more earlier… Thank You. I hope,(As all researchers are hoping)

38 References A computer model of child language learning, M Selfridge, Artificial Intelligence archive,Volume 29, Issue 2, Pages: CHILD DEVELOPMENT, Technology in early childhood education: Finding Balance Human brain works heavy statistics learning language, Jonathan Sherwood, University of Rochester Practice Builds Brain Connections For Babies Learning Language, How To Speak, Toshiaki Imada, Institute for Brain and Learning Sciences, University of Washington

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