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Share Your Data
Upload raw images, video, text, audio, or LiDAR securely — we ingest from cloud storage, SFTP, or your existing ML pipeline.
Audio transcription, speaker diarization, and acoustic event labeling for speech recognition and sound classification models.
Speech recognition, voice assistants, and acoustic event detectors need meticulously labeled audio — not rough transcripts. Our audio annotation services cover transcription, diarization, phonetic tags, and sound classification with multi-pass review aimed at low word-error rates in production.
Misheard proper nouns and missed speaker changes break downstream NLU. Annotators follow pronunciation guides, mark overlaps, and tag non-speech events so your acoustic models learn robust representations.
Full and verbatim transcription; speaker diarization and ID; phonetic and prosody labels; keyword spotting spans; environmental sound and alarm event tags; music vs speech segmentation.
Call center analytics, medical dictation, smart home voice commands, industrial machine monitoring, media subtitling corpora, and security audio event detection on edge devices.
Sample-batch WER measurement, glossary-driven review, and second-pass listening on flagged segments. Programs targeting sub-5% WER receive additional auditor layers.
JSON, CSV, and platform-native time-aligned exports compatible with major ASR training frameworks and custom fine-tuning pipelines.
Get speech and audio datasets built for production inference. Share sample clips, language mix, and WER goals — we design annotation guidelines and staffing for your acoustic ML program.
A proven calibration-to-production workflow for enterprise annotation programs.
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Upload raw images, video, text, audio, or LiDAR securely — we ingest from cloud storage, SFTP, or your existing ML pipeline.
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We define labeling guidelines, class taxonomy, edge cases, and accuracy targets with your ML and product stakeholders.
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Trained annotators label bounding boxes, masks, tracks, transcripts, or 3D cuboids in your toolchain or our workspace.
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Multi-pass review, consensus scoring, and automated checks before any dataset reaches your training jobs.
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Receive COCO, JSON, Pascal VOC, or custom exports — plus ongoing support as your models and taxonomies evolve.
Answers about scope, quality, tooling, and delivery.
Transcription, speaker diarization, phonetic labeling, emotion tags, and acoustic event detection for speech and sound models.
Multi-pass review, domain glossary alignment, and WER-focused QA on sample batches before full-corpus delivery.
Yes. Industrial, call-center, and outdoor recordings with background noise are supported with tailored guidelines.
Talk to our enterprise team about volume, timeline, QA targets, and pricing.