(26 Qs Updated December 2025)
Benchmark Results
Sunbird v2 + Gemini 3 Pro leads!
The top‑achieving Kikuyu benchmark in this workflow is Workflow 3 – “Kikuyu (Akera + Gem3pro)”, with an average similarity score of 0.78 against the reference transcripts. This setup combines Akera’s Kikuyu‑focused ASR with Gemini 3 Pro for post‑processing/translation, and it consistently delivers the closest match to the ground‑truth text across the 26 audio clips—slightly outperforming the Omnilingual + Gemini and Omnilingual + MT + GPT‑5.1 pipelines, and dramatically better than the baseline GPT‑Realtime audio route in this test set.
Info
This workflow benchmarks multiple Kikuyu speech-to-text pipelines on the same audio dataset. It compares GPT‑4o audio, Akera GPT‑5.1, Gemini 3 Pro, Omni and Kikuyu → English pipelines with Google Machine Translation.
Workflows covered
- GPT‑4o Audio – Kikuyu ASR
- Akera + MT + Gemini3 Pro
- Akera + GPT‑5.1 – Kikuyu-focused ASR & NLP
- Omnilingual + Gemini3 Pro– Kikuyu → English
- Omnilingual + MT + Gemini3 Pro – multimodal Kikuyu ASR
- Omnilingual + MT + GPT-5.1
Data & Evaluation
Kikuyu audio & reference transcripts from Google Sheets
Automated evaluator: compare-output-text-from-input_audio for text similarity and quality scoring.
Ideal for teams comparing Kikuyu speech recognition, Kikuyu audio transcription, and Kikuyu → English translation for call centers, media, education, and African-language AI applications.
Keywords: Kikuyu speech-to-text, Kikuyu ASR, Kikuyu audio transcription, Kikuyu to English translation, Akera AI Swahili, GPT‑4o audio Kikuyu, Gemini Pro Kikuyu transcription, Google MT Kikuyu.