Ocular AI (YC W24)

Founded 2024

Source high-fidelity conversational voice datasets and benchmark frontier speech models

You can use Ocular AI to source human-generated training datasets and evaluate speech models against realistic conversational benchmarks. The system connects frontier AI developers with domain experts to capture natural multi-speaker conversations, full-duplex audio, and specialized dialogue across dozens of languages. You can access benchmark leaderboards to measure word error rates and speaker diarization accuracy across frontier models. It provides custom annotation pipelines, emotional tagging, and human preference signals to improve voice agents, text-to-speech engines, and automated transcription systems for production environments.

What Ocular AI (YC W24) does

Benchmark speech-to-text models using word error rate metricsEvaluate speaker diarization accuracy across multi-speaker audioOrder custom conversational datasets for speech model trainingCollect domain-specific voice data with verified expertsGenerate human preference labels for audio fine-tuningTranscribe and annotate speech recordings at word levelFull-duplex conversational audio datasets with isolated channelsSpeaker diarization and speech-to-text public benchmarksExpert data foundry connecting researchers with domain specialistsFine-grained prosodic markers and continuous emotional taggingPhonetically balanced scripted audio for voice synthesisAudio dataset support across more than 40 languages