Ashutosh Jha's starred repositories
leetcode_company_wise_questions
This is a repository containing the list of company wise questions available on leetcode premium
django-compressor
Compresses linked and inline javascript or CSS into a single cached file.
flutter-architecture-blueprints
Flutter Architecture Blueprints is a project that introduces MVVM architecture and project structure approaches to developing Flutter apps.
direct-select-flutter
DirectSelect is a selection widget with an ethereal, full-screen modal popup displaying the available choices when the widget is interact with. https://dribbble.com/shots/3876250-DirectSelect-Dropdown-ux
flutter_cache_manager
Generic cache manager for flutter
Python_and_the_Web
Build Bots, Scrape a website or use an API to solve a problem.
Speech-enhancement
Deep learning for audio denoising
parabeac_core
Continuous Design / Continuous Integration for Figma to Flutter
flutter_background_fetch
Periodic callbacks in the background for both IOS and Android. Includes Android Headless mechanism
voice_activity_detection
Voice Activity Detection based on Deep Learning & TensorFlow
app_settings
Flutter plugin for accessing app phone settings for iOS and Android
liquid_progress_indicator
A liquid progress indicator for Flutter
StreamDeck-Discord
Control the Discord application with the Elgato StreamDeck
Speech_Signal_Processing_and_Classification
Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].
Flutter-route-transition
Repo for blog: Everything you need to know about Flutter page route transition
MarStech_Vision_Sensor
MarStech vision sensor is a low cost sensor for STEM Education
Speech_Feature_Extraction
Feature extraction of speech signal is the initial stage of any speech recognition system.
flutter_overboard
Onboarding widget for flutter to create beautiful onboarding slides with minimal code.
blemulator_flutter
BLEmulator Flutter: the Flutter BLE peripheral simulator
email-service
Python package to quickly integrate different email services with your Application with just 3 lines of code.
assemble-avengers
A dead-simple CLI tool to arrange a google meet call and send the link to the telegram group.
Sentiment-Analysis-CNN
A CNN approach to perform Sentiment Analysis on IMDB Movie Reviews Dataset