Speech Recognition and Correction of a Stuttered Speech
Objective
Develop a robust system for speech recognition and real-time correction of stuttered speech, aiming to enhance communication fluency and improve the overall user experience. The project will employ advanced signal processing, machine learning, and natural language processing techniques.
Abstract
Creating an algorithm to improve voice recognition of a stuttering speech is the goal of this work. Stuttering is a disease that causes involuntary repetition, lengthening of words or syllables, or involuntary silence pauses, all of which impair speaking fluency. Stuttered speech is not recognized by the speech recognition systems in use today.
Stutter detection methods have been documented in the literature, however effective stutter repair methods have not. This essay tackles the problem and suggests techniques for stutter detection and correction within reasonable time constraints. The development of amplitude thresholding via neural networks is intended to eliminate prolongation(s) from the sample.
Using an existing Text-to-Speech (TTS) system, repetitions are eliminated using a string repetition reduction technique. As a result, the output signal produces improved speech recognition because it is free of any stutters.
Keywords: Speech Recognition, Stutter, Neural Networks, STT system, TTS system.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is Signal Processing?
· About Signal Processing
· Introduction to Signal Processing
· How analog and digital signal is formed
· Importing the signal via signal acquisition tools
· Analyzing and manipulation of signals.
· Phases of signal processing:
· Acquisition
· Signal enhancement
· Signal restoration
· Medical Signal Processing
· Medical Signal Analysis
· Medical Signal Diagnosis
· Filtering techniques
· Machine Learning Algorithms
· Deep Learning Algorithms etc.
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
