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Voice based chat-bot for College Management System

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Abstract:

In this paper, we will create dataset about college details like staff details and college events, function etc.  Then, first we have to create one android app for using speech recognition. This paper presents the design and development of an intelligent voice recognition chat bot. The paper presents a technology demonstrator to verify a proposed framework required to support such a bot (a web service). So, using that chatbot android application, we can give speech input about college details. Then it will show response as text information.  While a black box approach is used, by controlling the communication structure, to and from the web-service, the web-service allows all types of clients to communicate to the server from any platform. The service provided is accessible through a generated interface which allows for seamless XML processing; whereby the extensibility improves the lifespan of such a service. By introducing an artificial brain, the web-based bot generates customized user responses, aligned to the desired character. Questions asked to the bot, which is not understood is further processed using a third-party expert system (an online intelligent research assistant), and the response is archived, improving the artificial brain capabilities for future generation of responses.

 

Existing method:

Conventionally web-bots exist; web-bots were created as text based web-friends, an entertainer for a user. Furthermore, and separately there already exists enhanced rich site summary (RSS) feeds and expert content processing systems that are accessible to web users. Text-based web-bots can be linked to function beyond an entertainer as an informer, if linked with, amongst others, RSS feeds and or expert systems. Such a friendly bot could, hence, also function as a trainer providing realistic and up-to-date responses.

Dragon speech recognition software is a Naturally Speaking Language. This software has three primary features of functionality.

  1. Dictation
  • As User dictates the words it will converts it into text and it displays
  1. Text-To-Speech
  • And as text what is present or selected can be converted to speech.
  1. Command Input
  • User can control the operation by means of his voice without using keyboard by just giving commands.

 

Disadvantage:

  1. Translation:
  • It cannot translate from one language to another language here comes translation problem.
  1. Untrained:
  • It cannot work without training, training is required, dynamic acceptance is not present.

 

Proposed System:

Speech recognition for application Voice Message is done on Google server, using the HMM algorithm. HMM algorithm is briefly described in this part. Process involves the conversion of acoustic speech into a set of words and is performed by software component. Accuracy of speech recognition systems differ in vocabulary size and confusability, speaker dependence vs. independence, modality of speech (isolated, discontinuous, or continuous speech, read or spontaneous speech), task and language constraints. Speech recognition system can be divided into several blocks: feature extraction, acoustic models database which is built based on the training data, dictionary, language model and the speech recognition algorithm.

 

Advantage:

  1. Speech recognition systems, based on hidden Markov models are today most widely applied in modern technologies.
  2. They use the word or phoneme as a unit for modeling.
  3. The model output is hidden probabilistic functions of state and can’t be deterministically specified.
  4. State sequence through model is not exactly known.

 

 System Architecture:

 

Hardware and Software Specification:

Hardware:

  1. OS – Windows 7,8 (32 or 64 bit)
  2. RAM – Min 2GB

 

Software:

  1. JDK
  2. Android Eclipse (ADT Bundle)
  3. Netbeans IDE
  4. Mysql and SQLyog.
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  • Instructor pantech team
  • Duration 15 Hrs
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  • Access 3 Months

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