Speechmatics provides speech-to-text for real-world audio with accurate transcription, diarization, and language coverage. Handle accents, noise, and overlapping speakers with advanced models. Use custom vocabulary and redaction. With batch or streaming APIs, timestamps, and quality metrics, teams build searchable media, call analytics, captions, and voice workflows.
Models trained on diverse conditions handle accents, domain terms, and crosstalk. Confidence scores and word timings reveal certainty so editors know what to review. With robust diarization and punctuation, transcripts read naturally and map to speakers. This reliability lifts downstream tasks like NER, search, and analytics, reducing manual cleanup and speeding delivery of usable results.
Transcribe live streams with low latency or process archives at scale. WebSocket and REST endpoints keep integration straightforward. Partial results update as audio arrives, while finalization locks segments for review. Because the same models power both modes, quality remains consistent. Teams unify live captions, VOD archives, and analytics pipelines without juggling separate tools.
Upload word lists and pronunciations to boost accuracy for brands, jargon, or names. Replace or mask sensitive data for compliance. These controls make transcripts safer to share with partners and downstream systems. With tunable vocabulary and privacy features, organizations build ASR into workflows confidently, keeping proprietary details protected while improving recognition on key terms.
Identify speakers and produce stable timestamps for quotes, highlights, and chaptering. Rich formatting preserves lists and emphasis from slides or scripted reads. Editors jump to moments reliably, which speeds review and content packaging. With structure aligned to media uses, teams turn raw speech into assets for captions, summaries, and search in minutes rather than hours of scrubbing.
Dashboards track throughput, error rates, and domains. Spot drift, compare model versions, and alert on anomalies. With metrics visible, owners manage costs and quality proactively. Since evidence guides upgrades and vocabulary tweaks, results improve steadily. Stakeholders trust outputs when they can see performance, which keeps projects moving and avoids fire drills during releases.
Best for media teams, platforms, and contact centers that need dependable ASR under messy conditions. With streaming and batch APIs, customization, diarization, timestamps, and quality signals, Speechmatics turns unpredictable audio into structured data. Editors, analysts, and engineers reduce cleanup, build reliable features, and deliver captions or insights that users trust across channels.
Speechmatics replaces brittle, one-size-fits-all transcription with a flexible platform tuned for real-world audio. It handles accents and noise, adapts vocabulary, and scales from live to archives with the same models. Because diarization, timing, and monitoring are built in, teams spend less time fixing errors and more time shipping captions, analytics, and search that feel accurate and timely.
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