PPT-CS460/626 : Natural Language

ProcessingSpeech NLP and the Web Lecture 36syllabification and transliteration Pushpak Bhattacharyya CSE Dept IIT Bombay 11 th April 2011 Access from one language to another . Processing/Speech, NLP and the Web. (Lecture . 29– CYK; Inside Probability; Parse Tree construction). Pushpak Bhattacharyya. CSE Dept., . IIT . Bombay . 22. nd. March, 2011. Penn POS Tags. [John/NNP ]. Language Processing. Lecture . 3. Albert . Gatt. 1. LIN3022 Natural Language Processing. Reminder: Non-deterministic FSA. An FSA where there can be multiple paths for a single input (tape).. Two . basic approaches . Processing/Speech, NLP and the Web. (Lecture . 33– . Phonetics and phonology). Pushpak Bhattacharyya. CSE Dept., . IIT . Bombay . . 31. st. March, . 2011. Ancient 5 x 5 Indian Classification of Consonants. Processing/Speech, NLP and the Web. (Lecture . 29– CYK; Inside Probability; Parse Tree construction). Pushpak Bhattacharyya. CSE Dept., . IIT . Bombay . 24. th. March, 2011. CYK Parsing. Shared Sub-Problems: Example. Ray Mooney. Department of Computer Science. University of Texas at Austin. Joint work with. David Chen. Joohyun. . Kim. Machine Learning and . Natural Language Processing (NLP). Manual software development of robust NLP systems was found to be very difficult and time-consuming.. Class Logistics. Quiz. Where is this quote from?. Dave Bowman. : Open the pod bay doors, HAL.. HAL. : I’m sorry Dave. I’m afraid I can’t do that.. Quiz Answer. “2001: A Space Odyssey” . 1968 film by Stanley Kubrick . Neural Networks from Scratch. Presented . By. Wasi Uddin . Ahmad. 3. rd. November, 2016. Written By. Denny . Britz. http://www.wildml.com/2015/09/implementing-a-neural-network-from-scratch/. "Lane, Mary E. . Processing/Speech, NLP and the Web. (Lecture . 9–IWSD; start of MT). Pushpak Bhattacharyya. CSE Dept., . IIT . Bombay . 24. th. Jan. , . 2011. Gloss. study. Hyponymy. Hyponymy. Dwelling,abode. bedroom. CS460/626 : Natural Language Processing/Speech, NLP and the Web (Lecture 28– Grammar; Constituency, Dependency) Pushpak Bhattacharyya CSE Dept., IIT Bombay 21 st March, 2011 Grammar A finite set of rules What is NLP?. “Natural” languages. English, . Hindi, . French, Swahili, Arabic, . Bangla, . ….. NOT Java, C++, Perl, …. Ultimate goal: Natural human-to-computer communication. Sub-field of Artificial Intelligence, but very interdisciplinary. Processing/Speech, NLP and the Web. (Lecture 1 – Introduction). Pushpak Bhattacharyya. CSE Dept., . IIT . Bombay. 4. th. Jan. , . 2011. . Persons involved. Faculty instructors: Dr. Pushpak Bhattacharyya (. 利 害 . li-hai. benefit-harm. standard selects social discourse . 道. . dao. guide. . Everyone's guiding rules, attitudes norms. Reform tradition--shocking results. . moral reform impasse. Partial solution: Rule out collectively self-defeating moralities. Abstract We discuss ways of allowing the users of a natural language processor to define, examine, and modify the definitions of any domain-specific words or phrases known to the system. An implement First Assignment. To be released over the weekend (due within the following week). 1. Today . What is Natural Language Processing?. Why is it hard? . Common Tasks in NLP. Language Modeling. Word and Sentence representations for ML.