Scoring and evaluation of user input in voice user interfaced intelligent interviewer chatbot (Record no. 6110)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02222nam a22001937a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220107122840.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 180604b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | IIITMK |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Anjana Anto (91616002) |
| 9 (RLIN) | 14284 |
| 245 ## - TITLE STATEMENT | |
| Title | Scoring and evaluation of user input in voice user interfaced intelligent interviewer chatbot |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | MSC MI 2016-2018 |
| 500 ## - GENERAL NOTE | |
| General note | Chatbot is a text based conversation agent which can interact human users through some<br/>medium, such as chat interface. Chat interface may be Conversational user interface or voice<br/>user interface. Conversational interface is a user interface design that allows users to chat with<br/>either real humans or bots. Conversational interfaces introduce an opportunity to interact with a<br/>machine using natural language. It takes two forms one is voice assistant that allows you to talk<br/>and other one is chatbots that allow you to type. Instead of using computer specific language,<br/>Conversational user interface enables users to talk to a computer the way they might talk to<br/>another human. This will become more advanced and more efficient. Here I-aBro is an education<br/>and learning chatbot that replace the conversational interface to VUI (voice user interface). VUI<br/>allows the user to interact user with both voice and speech commands. I-aBro generates both<br/>questions and answers and provides evaluation of users input. The main advantage of I-aBro is<br/>that the question is generated via previous response of the user’s input. And here we use Named<br/>Entity Recognition (NER) technology to generate the question, which made more reliable<br/>interview approach. I-aBro, the interview chatbot help to reduce human effort and it is a very<br/>time-consuming process. One of the challenge of I-aBro is to evaluate the interview. Evaluation<br/>is done in two ways. One method is Chat-log is converted to PDF format which sent via mail to<br/>of experts, and another method is evaluation by system itself which is done by Levenshtein<br/>Distance of users’ response. |
| 502 ## - DISSERTATION NOTE | |
| Degree type | MSC MI |
| Name of granting institution | 2016-2018 |
| Year degree granted | INT |
| -- | Mr. Pradeep Kumar K |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | CHATBOT |
| 9 (RLIN) | 14285 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | VOICE USER INTERFACE |
| 9 (RLIN) | 14286 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | NATURAL LANGUAGE PROCESSING |
| 9 (RLIN) | 14287 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Non Fiction | IIITM-K | Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre | 04/06/2018 | R-1404 | 04/06/2018 | 04/06/2018 | Project Reports |