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AI solutions for community radios
Open-source speech-to-text and searchable audio archive toolkits.
Our Open-Source Process for Speech-to-Text
and Searchable Audio Archive
Discover how we create accurate and searchable audio transcripts with our community-driven approach
Community-driven Voice Corpus Training
We leverage the power of our community volunteers to collect and label audio data using the Mozilla Common Voice project. This allows us to train our AI models with a diverse set of voices and accents for optimal performance.
Efficient Speech-to-Text Pipeline
We use state-of-the-art speech recognition algorithms to convert audio files to text, including support for multiple languages and dialects. Our pipeline is optimized for speed and accuracy, ensuring high-quality transcripts every time.
Transcript Indexing and Public Access
We index all transcripts for efficient search and retrieval, and make them publicly accessible for easy sharing and discovery. This also enables search engines to index the content, expanding the reach of your audio content.
Listen and learn about the future of audio transcription!
Ready to get started? Create and Account
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Who We Are?
Radioship has been designed and built by a diverse team including journalitsts, machine learning, natural language process experts, data scientists and service designers.
József Venczeli
data scientist
Orsolya Putz
data engineer
Gergely Gazda
product engineer
Edit Köles
project manager
Helga Fázold
journalist
Zoltán Varjú
NLP specialist
Emese Stork
service designerJózsef Venczeli
data scientistOrsolya Putz
data engineerGergely Gazda
product engineerEdit Köles
project managerHelga Fázold
journalistZoltán Varjú
NLP specialistEmese Stork
service designer