Turning 100+ hours of conversation into usable educational data.

Important conversations were happening across hours of multilingual audio.

Lets Talk Education needed to process extensive discussions, interviews and policy conversations involving multiple speakers.

Manually transcribing, translating and organizing this volume of audio would require significant time and effort.

Lucy transformed the conversations into structured data.

We delivered transcription and translation across Amharic, English, Tigrinya and Afaan Oromo, with the output provided in their selected format.

Lucy also used advanced audio synthesis and analysis to:

• Identify speakers
• Transcribe multi-speaker conversations
• Translate across languages
• Analyze conversation data
• Structure the resulting information
• Deliver outputs in their required format

100+ hours of conversations became usable information.

Instead of working through hours of raw recordings manually, Lets Talk Education received searchable, structured and analyzed outputs that could be used in their ongoing education initiatives.

The solution helped reduce manual workload and turnaround time while making multilingual stakeholder conversations easier to review, analyze and use.

The audio became data they could work with.

Lucy didn't simply convert speech into text.

The system helped transform lengthy conversations into structured information, including speaker identification, transcription, translation and advanced analysis, delivered in their chosen format.

This gave Lets Talk Education a more efficient way to review stakeholder discussions and extract useful information from large volumes of recorded conversations.

Four languages, one set of structured outputs.

• Amharic
• English
• Tigrinya
• Afaan Oromo

Supporting conversations across multiple languages allowed Lets Talk Education to work with a broader range of stakeholders while keeping the resulting information organized and accessible.