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Peggy SyloppPS

Peggy Sylopp

AI Engineer & Consultant (Audio & Speech)

$987/day
Berlin, DE
8-15 years
Python
Speech Processing
Data analysis
AI Prototyping
Audio Signal Processing

Average response time: 1 hour

About Peggy

I build AI systems for audio and speech applications that work in real-world environments, from prototyping to deployment.

My work combines machine learning, real-time audio processing, and user-centered design to create practical, high-impact solutions. I have experience developing AI-based personalization systems, mobile audio applications, and real-time voice interfaces.

I support teams in translating complex ideas into working systems — from initial concept and prototyping to implementation and evaluation in real-world contexts.

My focus areas include:
• Audio & speech processing (STT, TTS, signal processing)
• Conversational AI and real-time systems
• Machine learning models based on real-world user data
• Prototyping and applied AI development

In addition to implementation, I bring experience in project leadership and interdisciplinary collaboration, working across engineering, research, and applied domains.

I am particularly interested in projects involving conversational AI, audio technologies, and applications in healthcare and assistive systems.
Software Publishing
Digital and IT Services
Health and Wellness

  • German

    Native or bilingual

  • English

    Fluent

  • Italian

    Basic

Can work on-site
Berlin (up to 50km), Hamburg (up to 50km), Leipzig (up to 50km)

Experience

  • sinceare UG (Fraunhofer Spin-off)
    Founder & Technical Lead (AI & Audio Systems)
    TECH
    May 2022 - Today (4 years and 1 month)
    Berlin, Germany
    Led the development of AI-based personalization systems for hearing applications, focusing on real-world performance and user-centered design.

    Developed a mobile audio application (iOS, JUCE/C++) enabling real-time audio processing and interactive control of sound parameters, with a focus on low-latency performance and usability.

    Built machine learning models to predict user-specific sound preferences based on real-world data and listening environments, supported by data pipelines and feature engineering for audio-based models.

    Designed and implemented real-time audio processing systems, integrating ML components into functional, low-latency prototypes.

    Designed and conducted user studies to evaluate system performance in realistic environments, including speech intelligibility, listening effort, and user preference.

    Managed projects end-to-end, from concept and funding to implementation and real-world evaluation.

    Coordinated interdisciplinary teams across engineering, research, and clinical domains.

    Translated a patented AI method for individualized sound personalization into an applied software system.
    Machine Learning Data analysis Feature Engineering Audio Signal Processing User Research
  • sinceare UG (Fraunhofer Spin-off)
    AI Engineer – Conversational AI Systems
    SOFTWARE PUBLISHING
    November 2025 - November 2025
    Additionally, developed a real-time conversational AI system (Voice Bridge / Hörstimme), implementing a full-duplex STT–TTS audio streaming pipeline in the browser.

    Built a low-latency audio processing system using Web Audio API, including speech detection and adaptive chunking strategies.

    Developed multiple streaming modes (interval, silence-based, hybrid) to optimize latency and user experience.

    Integrated backend services (FastAPI + STT/TTS APIs) with real-time playback via MediaSource API.

    → Result: end-to-end conversational AI system bridging speech recognition, synthesis, and real-time interaction.
    Conversational AI Speech Processing Real-time Systems Python Text-to-Speech (TTS)
  • Fraunhofer IDMT
    Project Lead – AI & Hearing Research
    SOFTWARE PUBLISHING
    November 2017 - February 2021 (3 years and 3 months)
    Berlin, Germany
    Led a research and development project on personalized hearing technologies, from initial concept to proof-of-concept system.

    Conceived and led the project “Hear How You Like to Hear”, focusing on AI-based sound personalization.

    Secured public funding and managed project execution, including planning, coordination, and delivery.

    Coordinated interdisciplinary teams across engineering, research, and user-focused domains.

    Developed proof-of-concept systems for machine learning-based sound personalization, grounded in real-world user needs.

    → Result: patented AI-based method for individualized sound personalization.
    Machine Learning Project Management User Research Research and Development (R&D) Data science

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Education

  • M.A. Public
    HUMBOLDT-VIADRINA SCHOOL OF GOVERNANCE
    2011
    M.A. Public
  • Diploma in Computer Science
    TU BERLIN
    2009
    Diploma in Computer Science

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