Design and Development of Speech Database for Travel Purpose in Marathi (original) (raw)
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IOSR Journal of Computer Engineering, 2014
The paper represents the brief information about developing speech database in Marathi language for Travel purpose in Aurangabad District. Development of speech database is very primary requirement for developing an Automatic Speech Recognition System. The accuracy of speech recognition depends on the quality of the speech data recorded and the algorithms implemented for the development of ASR. The data collection procedure from various speakers from Aurangabad district is described in the paper for developing ASR system in Marathi language for travel domain.
Speech is a natural means of communication between humans. Human being tried to develop computer that can understand & talk like human. Digital content can research to the masses & facilitate the exchange of information across peoples speaking different language in form of natural interface provided by language technologies. Developing certain recognition system standard, speech database is a prerequisite. There is lot of scope to develop automatic speech recognition (ASR) system using Indian languages which are of different variations. This paper present review on speech database developed for Marathi language.
Marathi Speech Database Standardization:A Review and Work
Vol. 19 No. 7 JULY 2021 International Journal of Computer Science and Information Security (IJCSIS), 2021
Automatic Speech Recognition System (ASR) is helpful for interaction between human and machine. It is the way to operate computer and mobile phones through speech only, without taking such extra efforts. The term corpus is used for Standardized Database, which contains a collection of audio recordings of spoken language with its annotations and documents. When existing literature was reviewed, it was observed that much literature is available on how to create speech databases. But few literatures are available about the standardization. Such work is done for the languages other than Indian languages. But for the Hindi, Marathi etc., standardization for the speech datasets is not up to the mark. The main problem in designing of a speech database is to deal with variability of speech. In recent years, there is much need to develop speech corpora for training and testing materials to be used for wide range of applications of speech technology like Linguistic Consortium, Speech interfaces development and language models etc. If it is standardized in regional languages, it will certainly contribute in many applications and research. In future, we would like to work to find standard way to standardized speech databases so with the help of this we can retrieve data easily and more efficiently.
Design and Development of Speech Database of Marathi Numerals
This paper describes the approach followed for development of speech database of Marathi digits starting from Shunya (zero) up to Nau (nine). The following paper describes the step by step procedure followed for the development of the speech database. For the development of automatic speech recognition (ASR) it is necessary to have a speech databases and the recognition rate depends upon the quality of the used speech databases. I. INTRODUCTION Speech is the way communication between humans where human can share their information with each other. The researchers around the world are trying to develop new interface system for communication between human and computer. Speech is having the capability of being used as a mode of interaction between human and Computer. Estimated number of languages spoken around the world varies between 6,000 and 7,000. Language technologies can play a vital role in the natural interfaces for those who can't understand the particular language. The lan...
Implementation of Marathi Language Speech Databases for Large Dictionary
In this research paper, we discuss our efforts in the development of Marathi language speech databases in Marathi for building large vocabulary. We have collected speech data from about 5 speakers in these one languages. We discuss the design and methodology of collection of speech databases. We also present preliminary speech recognition results using the acoustic models created on these databases using Sphinx 2 and Festvox speech tool kit.
Indian Language Speech Database: A Review
International Journal of Computer Applications, 2012
Speech is the most prominent and natural form of communication between humans. Human beings have long been motivated to create computer that can understand and talk like human. When the research tries to develop certain recognition system they require certain previously stored data i.e. database for respective recognition system. There are various speech databases available for European Language but very less for Indian Language. In this paper we discuss the various Speech Database developed in different Indian Languages for speech recognition system & Text to Speech System.
IEEE xplore, 2013
In this paper, we discuss our efforts in the development of Indian spoken languages corpora for building large vocabulary speech recognition systems using WATSON Toolkit. The current paper demonstrates that these corpora can be reduced to a varied degree for various phonemes by comparing the similarity among phonemes of different languages. We also discuss the design and methodology of collection of speech databases and the challenges we have faced during database creation. The experiments have been conducted on commonly known Indian languages, by training the ASR system with WATSON toolkit and evaluation by Sclite. The results for these experiments show that different Indian languages have a great similarity among their phoneme structures and phoneme sequences and we have exploited these features to create speech recognition system. Also, we have developed an algorithm to bootstrapping the phonemes of one particular language into another by mapping the phonemes of different languages. The performance of Hindi and Bangla ASR systems using these databases has been compared.
Speech Recognition for Hindi Language
Speech is the most natural way of communication between human beings. The field of speech recognition generates intrigues of manmachine conversation and due to its versatile applications; automatic speech recognition systems have been designed. In this paper we are presenting a novel approach for Hindi speech recognition by ensemble feature extraction modules of ASR systems and their outputs have been combined using voting technique ROVER. Experimental results have been shown that proposed system will produce better result than traditional ASR systems.
A Review on Automatic Speech Recognition System in Indian Regional Languages
Speech Recognition is the system whose allows a user to use their voice in the form of input data. It may be used to command text to the computer and give order to the computer system. Speech technologies are commonly used available for an unlimited but most important range of tasks. Older speech recognition application needs to identify each single world by the different phases. This process allow to the machine to conclude where one word begins and the next word stops. This type of speech recognition application are still used to direct to the computer's system. And operate applications like web browser and spread sheets. New speech recognition system allow a user to order text fluently into the system. The system that allow continuous speech are generally designed to recognize text and format it, rather than controlling the computer system itself.in This research paper studied various types of techniques which is mostly used in automatic speech recognition.
IOSR Journal of Computer Engineering, 2014
Speech is a natural mode of communication for people. Yet people are so comfortable with speech, they would also interact with the computers via speech, and various interfacing devices such as keyboards and pointing devices. Outstanding work in speech recognition and computing has produced the commercial speech recognition systems for voice driven computing and word-processing systems. The analysis within the space of speech recognition lots of work is done for English language and European language and the opposite hand very little work done for Indian language and really little in Marathi. Only Because of This We Develop Automatic Speech Recognition of Isolates Marathi Words For Agriculture Purpose. For developing ASR system we use hybrid feature extraction technique i.e. MFCC with RASTA and for recognition Dynamic Time Wrapping is used.