Project Title: Expert Audio DSP Engineer for "Sonic Signature" Replication (Linux CLI Tool) > > --- The Core Mission --- > > We are looking for a world-class Audio DSP expert for a highly ambitious and unique project. This is NOT a standard audio conversion task. > > Our goal is to create an intelligent audio processing system that can replicate a very specific, beloved "sonic signature" found in the output of the classic ClipConverter service. We want to apply this signature consistently across ANY input video/audio file (dialogue, music, mixed content, etc.), making them all share the same warm, intimate, and clean audio profile. > > The target "feel" is defined by two reference files: "Audio.mp3" and "audio.mp3". The final output must be psychoacoustically indistinguishable from these references for a trained ear. > > **--- The Challenge: Building the "Magic System" ---** > > We envision a two-stage solution: > > **Stage 1: Reverse Engineering the "Sonic Signature"** > * Perform a deep, forensic analysis of the reference files ("Audio.mp3", "audio.mp3") against their original sources. > * Reverse-engineer the exact processing chain used to create them. This is likely a specific combination of high-pass filtering, multi-band compression, dynamic EQ, limiting, and other DSP techniques. > * The deliverable is a set of precise parameters (a "Preset") that, when applied to the original source, perfectly recreates the reference file. > > **Stage 2: Developing the Universal Application System** > * The core challenge: A single, fixed preset will not work universally across different audio types (e.g., a preset for music will fail on dialogue). > * We need a system that can intelligently apply the "sonic signature" to any source. This will likely involve: > 1. **Content-Type Detection:** The system must first analyze the input audio to identify its primary category (e.g., dialogue, music, nature sounds, urban noise). > 2. **Adaptive Parameter Sets:** You will develop several distinct parameter sets (presets), one for each audio category, all tuned to deliver the same final "sonic signature". > 3. **Automatic Application:** The program will then automatically select and apply the correct parameter set based on the detected content type. > > This is a research and development project that requires creativity, systematic experimentation, and a deep understanding of audio science. > > **--- Technical Environment & Deliverable Requirements ---** > > * **Final Deliverable:** The final product must be a standalone **Command-Line Interface (CLI) tool** that runs on a **Linux** server. A graphical user interface (GUI) is NOT required. > * **Target Environment:** The tool will be deployed and run on a standard Linux VPS (Virtual Private Server). > * **User Interaction:** The client (myself) will operate this tool from an **Android phone** using a terminal app (like Termius) to connect to the Linux VPS. The tool must be operable through simple command-line arguments. > * **Testing Collaboration:** The developer is not required to have their own Linux system for testing. The client will be responsible for testing the builds on the target VPS and providing feedback/error logs. > > **--- What We Are Looking For: ---** > * Deep, proven expertise in Digital Signal Processing (DSP), psychoacoustics, and audio engineering. > * Demonstrable experience in reverse-engineering audio processing chains. > * Advanced skills in developing cross-platform or Linux-native audio processing algorithms (Python, C++, etc.). > * Familiarity with command-line tools like FFmpeg and SoX is essential. > * Experience with machine learning for audio or content-type detection is a major plus. > > **--- What We Are NOT Looking For: ---** > * Someone who will only apply a basic, fixed FFmpeg filter chain. > * Someone who can only build Windows-based applications. > * Someone who cannot explain the "why" behind their processing choices. > > **--- How to Apply ---** > Please begin your proposal with the phrase **"SONIC SIGNATURE"** so we know you have read and understood the complexity of this unique challenge. > > In your proposal, please confirm your comfort with developing a Linux CLI tool and collaborating on the testing process as described above. Provide your initial thoughts on how you would approach this problem, specifically the challenge of applying a consistent signature to varied content.