Speech Recognition Database Management with python

Overview

Speech Recognition Database Management

The main aim of this project is to recognize voice of the user as input and convert that input voice into the text form.

Libraries Used Inside the Project

We have used Speech Recognition module of Python to accomplish this mission. Inside it we have modules like PyAudio which helps us to play and record audio.

Libraries

Also, we have used the MySQL connector module for connecting our Python program to our MySQL database.

2

Libraries Created During the Project

We have created a library named MySQLvoice which helps our Artificial Intelligence to manage and organise the databases.

3

The main aim of this module is to select the keywords from the given input. After selecting the keywords our Artificial Intelligence start working on the database and provide the required results.

How We Converted the Voice into Text

For getting the voice input of the user we have used the pre-build library of Python which is Speech Recognition. We have taken the voice input from the systems microphone and stored it into a variable. After that we used the recognize function of Speech Recognition to recognize what user said and stored it into a variable.

After recognizing we printed the input into the text form to check the durability of our program.

4

Description

Using MySQLvoice library user doesn't need to know SQL database languages to make any changes or to know anything about their database. We have announced eight new keywords as follows:

5

How to Install and Run the Project

Once the MySQLvoice pip package is uploaded on PyPI, you can directly write "pip install MySQLvoice" in your respective terminals to install it in your system. After installing you can import it in your Python compiler and get benefited.

How to Use the Project

This Project is limited to MySQL Database operations but it can be used in all regions of the world for handeling databases as it is very easy to develop for regional languages. We are mostly working in common English language but it has the capability to be coded for any languages spoken in the world like Kannada, Korean, Japenese, Hindi, Gujrati etc. It will help the Non-Technical person to handle databases with ease.

Advantages

  1. It supports multitasking.

  2. Users don’t need to code.

  3. Can be used in any sector of industry where we employ databases.

  4. It saves time of the user which will enhance work procedure and economy.

Disadvantages

  1. May fail to work during hardware failure.

  2. May take time in data training of speech recognition.

  3. Noise pollution can hamper the quality of voice input.

  4. The improper pronunciation can effect the voice input.

Future Plans

We dream to include the regional languages (such as Kannada, Gujarati, Marathi etc.) which will help non-technical person to handle their databases.

We have a plan to include this developer tool features to small scale industries to enhance their productivity with this time saving database handling.

Conclusion

This project will help a lot of indutries and business as they are able to manage and organize their databases with thier voice. Also it will reduce the work load to a greater extent.

This project is just a small example of Artificial Intelligence related Database Management.

This project was jointly created by:

6

Owner
Abhishek Kumar Jha
Abhishek Kumar Jha
NLP, Machine learning

Netflix-recommendation-system NLP, Machine learning About Recommendation algorithms are at the core of the Netflix product. It provides their members

Harshith VH 6 Jan 12, 2022
Python generation script for BitBirds

BitBirds generation script Intro This is published under MIT license, which means you can do whatever you want with it - entirely at your own risk. Pl

286 Dec 06, 2022
基于“Seq2Seq+前缀树”的知识图谱问答

KgCLUE-bert4keras 基于“Seq2Seq+前缀树”的知识图谱问答 简介 博客:https://kexue.fm/archives/8802 环境 软件:bert4keras=0.10.8 硬件:目前的结果是用一张Titan RTX(24G)跑出来的。 运行 第一次运行的时候,会给知

苏剑林(Jianlin Su) 65 Dec 12, 2022
Code for the paper "Flexible Generation of Natural Language Deductions"

Code for the paper "Flexible Generation of Natural Language Deductions"

Kaj Bostrom 12 Nov 11, 2022
TTS is a library for advanced Text-to-Speech generation.

TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. TTS comes with pretra

Mozilla 6.5k Jan 08, 2023
Share constant definitions between programming languages and make your constants constant again

Introduction Reconstant lets you share constant and enum definitions between programming languages. Constants are defined in a yaml file and converted

Natan Yellin 47 Sep 10, 2022
This project aims to conduct a text information retrieval and text mining on medical research publication regarding Covid19 - treatments and vaccinations.

Project: Text Analysis - This project aims to conduct a text information retrieval and text mining on medical research publication regarding Covid19 -

1 Mar 14, 2022
ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.

ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.

Antlr Project 13.6k Jan 05, 2023
NLTK Source

Natural Language Toolkit (NLTK) NLTK -- the Natural Language Toolkit -- is a suite of open source Python modules, data sets, and tutorials supporting

Natural Language Toolkit 11.4k Jan 04, 2023
Code for CodeT5: a new code-aware pre-trained encoder-decoder model.

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation This is the official PyTorch implementation

Salesforce 564 Jan 08, 2023
Code for ACL 2022 main conference paper "STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation".

STEMM: Self-learning with Speech-Text Manifold Mixup for Speech Translation This is a PyTorch implementation for the ACL 2022 main conference paper ST

ICTNLP 29 Oct 16, 2022
Understanding the Difficulty of Training Transformers

Admin Understanding the Difficulty of Training Transformers Guided by our analyses, we propose Adaptive Model Initialization (Admin), which successful

Liyuan Liu 300 Dec 29, 2022
A Practitioner's Guide to Natural Language Processing

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, Text

Dipanjan (DJ) Sarkar 1.5k Jan 03, 2023
SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering.

SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. Contents Inst

0 Oct 21, 2021
TruthfulQA: Measuring How Models Imitate Human Falsehoods

TruthfulQA: Measuring How Models Imitate Human Falsehoods

69 Dec 25, 2022
A Japanese tokenizer based on recurrent neural networks

Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following

325 Jan 05, 2023
Code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".

This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".

Chenhe Dong 28 Nov 10, 2022
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

ASAPP Research 67 Dec 01, 2022
Pytorch NLP library based on FastAI

Quick NLP Quick NLP is a deep learning nlp library inspired by the fast.ai library It follows the same api as fastai and extends it allowing for quick

Agis pof 283 Nov 21, 2022
Official PyTorch implementation of SegFormer

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page

NVIDIA Research Projects 1.4k Dec 29, 2022