This project is an AI meeting assistant and interview copilot that monitors system audio and screen content to generate real-time responses during video calls. It functions as a system audio transcription tool and a context-aware prompt manager, injecting user documents and behavioral profiles into large language model prompts to tailor AI outputs. The system features a stealth screen overlay, utilizing a transparent window that displays information on top of other applications while remaining invisible to screen-sharing software and proctoring tools. It employs a process-hiding mechanism to
Cheetah is an LLM technical interview assistant composed of a native macOS application and a browser extension. It provides real-time coding and answering suggestions during technical interviews by combining live audio transcription with web-based context extraction. The system functions as a real-time interview coach that converts spoken questions into text using on-device speech-to-text processing. It uses a browser-integrated DOM scraper to extract live code and console logs, allowing the AI to analyze the current coding state and generate technical solutions based on the specific environm
Authboss is a modular authentication framework designed to manage user identity and account orchestration. It provides a comprehensive system for handling user registration, email verification, and the full lifecycle of user profiles. The framework distinguishes itself through a focused suite of security and identity tools, including multi-factor authentication via time-based passwords and SMS, and identity integration with external providers using OAuth1 and OAuth2 protocols. It also includes a dedicated account security manager that implements brute-force protection through credential-based
PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams into written text without requiring a network connection. It functions as a speech-to-text library, a real-time transcription engine, and a voice command processor, capable of detecting and transcribing spoken commands from continuous audio streams with configurable acoustic and language models. The engine uses weighted finite-state transducers to represent acoustic, phonetic, and language models as a single search graph for efficient decoding. It employs fixed-point acoustic mod
This project is a suite of tools centered around an AI-powered interview assistant, a professional resume builder, and an engineering salary database. The core application provides real-time audio transcription and generates code and system design solutions during technical interviews.
Principalele funcționalități ale ibttf/interview-coder sunt: Real-Time Interview Copilots, AI-Powered Code Generation, Real-Time Transcription, Real-Time Audio Transcribers, Keyboard-Driven Interfaces, Stealth Interface Shortcuts, Salary Benchmarking Databases, Audio Processing.
Alternativele open-source pentru ibttf/interview-coder includ: sohzm/cheating-daddy — This project is an AI meeting assistant and interview copilot that monitors system audio and screen content to… leetcode-mafia/cheetah — Cheetah is an LLM technical interview assistant composed of a native macOS application and a browser extension. It… volatiletech/authboss — Authboss is a modular authentication framework designed to manage user identity and account orchestration. It provides… cmusphinx/pocketsphinx — PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams… thewh1teagle/vibe — Vibe is a cross-platform transcription tool that converts spoken audio into text by running Whisper neural models… const-me/whisper — Whisper is a high-performance speech-to-text inference engine that uses graphics hardware shaders to accelerate the…