Indian Language Speech Database: A Review

Shrishrimal, Pukhraj P.; Deshmukh, Ratnadeep R.; Waghmare, Vishal B.

doi:10.5120/7184-9893

Cited by 34 publications

(11 citation statements)

References 4 publications

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“…Also research is going in institutes like IIT-M, C-DAC, TIFR, IIIT Hyderabad, IIT-Bombay, IIT-Kharagpur and various universities related to Marathi language for building of corpus, POS taggers, onlinesynthesizers [20]. The novelty of this research is intended to build application oriented systems, which is small and easily accessible to common people using Marathi language [21].…”

Section: Literature Surveymentioning

confidence: 99%

Implementation of Concatenation Technique for Low Resource Text-To-Speech System Based on Marathi Talking Calculator

Mundada

Kayte

Das

2018

6th Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU 2018)

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The indulgent acquaintance of mathematical basic concepts creates the pavement for numerous opportunities in life for every individual, including visually impaired people. The use of assertive technology for the disabled section of the society makes them more independent and avoid barriers in the field of education and employment. This research is focused to design an Android-based application i.e. talking Calculator for low resource based Marathi native language. The novelty of this work is to develop both, the application and the Marathi number corpus. Marathi is an Indo-Aryan language spoken by approximately 6.99 million speakers in India, which is the third widely spoken language after Bengali and Telugu but as they lack in linguistic resources, e.g. grammars, POS taggers, corpora, it falls into the category of low resource languages. The front end part of the application depicts the screen of a basic calculator with numerals displayed in Marathi. During runtime, each number is spoken as the specific key is pressed. It also speaks out the operation which is intended to be performed. The concatenation synthesis technique is applied to speak out the value of decimal places in the output number. The result is spoken out with proper place value of a digit in Marathi. The performance of the system is measured to the accuracy rate of 95.5%. The average run time complexity of the application is also calculated which is noted down to 2.64 sec. The feedback and review of the application is also taken from real end-user i.e. blind people.

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Section: Literature Surveymentioning

confidence: 99%

Implementation of Concatenation Technique for Low Resource Text-To-Speech System Based on Marathi Talking Calculator

Mundada

Kayte

Das

2018

6th Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU 2018)

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“…There are various spoken languages which are used throughout the world. The communication among the human being is mostly done by vocally; therefore it is natural for expect speech intersection with computer [1].Since Speech recognition (SR) means translation spoken words to the text or commands. Speech recognition systems has but robustness and noise tolerant of the problems which make speech recognition systems inconvenient to use…”

Section: Analysis Of Clustering Techniquesmentioning

confidence: 99%

Analysis of Clustering technique

Jadhav¹,

Patil²

2018

IJTSRD

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Data mining technique has been considered as useful means for recognize patterns and accumulate of large set of data. This method is basically used to extract the unknown pattern from the large set of data as real time applications. It is an approximate intellect discipline which has appeared valuable tool for data analysis, new knowledge recognition and decision making. The speech recognition is also most important research area to find the speech signa by the computer. To evolve the recognition of the continuous speech signal, a speech segmentation, feature extraction and clustering techniques are used. The unlabelled data from the large dataset can be categorized initially in an unaided fashion by usi cluster analysis. The result of the clustering process and efficiency of its application are generally resolved through algorithms. There are various algorithms which are used to solve this problem. In this research paper two important clustering algori canter points based K-Means and representative object based FCM (Fuzzy C-Means) clustering algorithms are compared. The Hidden morkov model and Gaussian mixture model are the most suitable acoustic models are used to scale the continuous speech signal and recognize the corresponding text data.Keywords: Hidden Markov Model (HMM), Gaussian Mixture Model, k means and Fuzzy c means (FCM) clustering.

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“…Human beings have long been motivated to create computer system that can understand and talk like humans. In this direction, researchers are trying to develop systems which can analyze, classify and recognize the speech signals [1]. However, the emotion expressed by speech is one of the major influencing factors for the low recognition accuracy achieved during the development of speech based systems.…”

Section: Introductionmentioning

confidence: 99%

Development of Isolated Marathi Words Emotional Speech Database

Waghmare¹,

Deshmukh²,

Shrishrimal³

et al. 2014

IJCA

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The research work describes the procedure and the development of Isolated Marathi Emotional Speech Database. The database consists of samples, collected from 50 speakers including males and females who simulated the emotions producing by the Marathi utterances which are used in everyday communication and are interpretable in all applied emotions. The speech samples were enhanced by spectral subtraction method and distinguished by the various real life situations. The recorded speech samples were categorized in three basic categories i.e. Happy, Sad and Angry.

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Indian Language Speech Database: A Review

Cited by 34 publications

References 4 publications

Implementation of Concatenation Technique for Low Resource Text-To-Speech System Based on Marathi Talking Calculator

Implementation of Concatenation Technique for Low Resource Text-To-Speech System Based on Marathi Talking Calculator

Analysis of Clustering technique

Development of Isolated Marathi Words Emotional Speech Database

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