DICTIONARY APPLICATION WITH SPEECH RECOGNITION AND SPEECH SYNTHESIS

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PDF Sphinx-4: A Flexible Open Source Framework for Speech Recognition Speech Recognition in a Multi-speaker Environment by using Hidden Markov Model and Mel-frequency Approach Improving Domain-Independent Cloud-Based Speech Recognition with Domain-Dependent Phonetic Post-Processing Open source voice creation toolkit for the MARY TTS Platform Mathifier – Speech Recognition of Math Equations
Published: Feb 20, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i1.5155
Keywords:
Speech Recognition, Searching and Mapping, Speech Synthesis, Sphinx, Hidden Markov Model, MARY TTS

Main Article Content

Vijayendra Sanjay Gaikwad
ABMSP's Anantrao Pawar College of Engineering & Research
Akash Huchcheshwar Hulbutti
ABMSP's Anantrao Pawar College of Engineering & Research
Sanket Mohan Kamble
ABMSP's Anantrao Pawar College of Engineering & Research
Ajinkya Sham Kundur
ABMSP's Anantrao Pawar College of Engineering & Research
Shubham Prakash Thorve
ABMSP's Anantrao Pawar College of Engineering & Research

Abstract

In today’s environment while reading documents (online/offline) or browsing through many websites, we face many unfamiliar words, as we cannot get the meaning of those words we lack in complete understanding of the concepts or situations. So, to overcome this problem we are developing a speech to text and text to speech input output method for our Voice Based Dictionary system. The system will be implemented using Java Sphinx-4 API for speech synthesis and speech recognition. The application or the system uses Java concepts like Swing API, JavaFX for graphical user interface (GUI) the system will be deployed in the background process using Java multi-threading support.

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Article Details

Issue
Vol. 9 No. 1 (2018): January-February 2018
Section
Articles

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References

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S. Batlouni, H. Karaki, F. Zaraket, F. Karameh, “Mathifier – Speech Recognition of Math Equationâ€,18th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2011, Beirut, Lebanon, December 11-14, p. 301, 2011.

Information retrieved on November 10th, 2017, from http://www.guidogybels.eu/asrp4.html.

J. Watada,IEEE ,Hanayuki. “Speech Recognition in a Multi-Speaker Environment by using Hidden Markov Model and Mel-frequency Approachâ€, Third international conference on computing measurement control and sensor network.

S. Pammi,M. Charfuelen,M. Schröder, â€Multilingual Voice Creation Toolkit for MARY TTS Platformâ€.

Documentation retrieved on October 20th, 2017 from, mary.dfki.de/documentation/index.html.