maxi1571/speech_recognition_dashoard

African language Speech Recognition Dashboard

In this project we are building a dasboard for our deep learning model that converts Ahmaric speech to text/voice to text format.

Table of Content

• Introduction

Introduction

The World Food Program wants to deploy an intelligent form that collects nutritional information of food bought and sold at markets in three different countries in Africa - Ethiopia and Kenya.

The design of this intelligent form requires selected people to install an app on their mobile phone, and whenever they buy food, they use their voice to activate the app to register the list of items they just bought in their own language. The intelligent systems in the app are expected to live to transcribe the speech-to-text and organize the information in an easy-to-process way in a database.

Our responsibility was to build a deep learning model that is capable of transcribing a speech to text. The model we produce should be accurate and is robust against background noise.

The model has been built here.We now want to creata a dashboard that can show case how our model works.

The dashboard will take in speech/voice of a person as input and give the text format of the speech as output.

Contributors

1. Natnael Sisay
2. Elias Andualem
3. Ethani Caphace
4. Behigu Gizachew
5. Michael Tekle Woji
6. Fumbani Banda
7. Christian ZANOU
8. Robert Ssebudandi