Live and batch speech recognition
Support streaming sessions, uploaded files, archives, interim results, finalized segments, and model routing.
Accessibility, Language & Privacy
Turn live and recorded speech into synchronized transcripts, captions, subtitles, translations, searchable media, and localized content across calls, meetings, education, healthcare, broadcast, and video archives.
Speech-to-text is only one component. A production workflow must preserve speakers, timestamps, terminology, media synchronization, subtitle timing, correction, translation, indexing, playback, permissions, and operating quality. OPTIME engineers that complete media-intelligence path.
WHY THIS MATTERS
A basic STT API returns text.
Turn live and recorded speech into synchronized transcripts, captions, subtitles, translations, searchable media, and localized content across communications, education, healthcare, broadcast, and enterprise video.
SYSTEM PRESSURES
Text without accurate speaker and timestamp context cannot support captions, search, review, or playback.
Names, products, medical terms, financial terms, technical language, and proper nouns require controlled vocabulary.
Reading speed, segmentation, line length, timing, placement, and format matter.
Localized output may lose source timing, speaker identity, and correction state.
Transcript files may not be connected to media, topics, chapters, entities, and semantic retrieval.
Sensitive audio, recordings, and transcripts may require private or regional processing.
COMPLETE SOLUTION
The complete system can connect live STT, batch STT, language detection, diarization, timestamps, custom vocabulary, correction, captions, subtitle segmentation, SRT, WebVTT, applicable broadcast formats, translation, localization, voice-translation integration, chapters, topics, semantic search, indexed playback, private inference, WebRTC, broadcast, archive processing, APIs, operational controls.
CAPABILITY GROUPS
Support streaming sessions, uploaded files, archives, interim results, finalized segments, and model routing.
Identify configured speakers where supported, diarize turns, detect language, and preserve participant and session context.
Apply custom vocabulary, names, domain terms, correction interfaces, dictionaries, and reviewer feedback.
Deliver captions to WebRTC calls, meetings, streams, applications, or broadcast workflows.
Create timed segments, line breaks, reading constraints, SRT, WebVTT, and other approved formats.
Generate translated captions, subtitles, metadata, and localized media variants with review and source traceability.
Index transcripts, speakers, topics, chapters, entities, keywords, semantic meaning, and timestamps.
Combine speech with slides, OCR, documents, visual events, program metadata, or application context.
Run models on-premises, in private cloud, at the edge, regionally, or in disconnected environments.
Measure word or task quality, terminology, speaker behavior, latency, synchronization, corrections, model versions, and failures.
ARCHITECTURE FLOW
The flow begins with call, meeting, live stream, broadcast, classroom, clinical session, or recording and preserves control through every processing and operating layer.
Call, meeting, live stream, broadcast, classroom, clinical session, or recording
Audio extraction, normalization, timing, and media identity
Streaming or batch STT
Speaker, language, terminology, confidence, and correction
Transcript and synchronized media timeline
Caption and subtitle segmentation
Translation, localization, and optional voice-translation integration
Topic, chapter, entity, keyword, and semantic indexing
Search, playback, applications, APIs, and downstream systems
Evaluation, privacy, model versions, infrastructure, and operations
ARCHITECTURE DECISIONS
Approach A
Live
Approach B
batch processing
Selection considerations
Choose according to result timing, quality, context, infrastructure, and user experience.
Approach A
Generic
Approach B
domain-specific models
Selection considerations
Use vocabulary, adaptation, specialist models, and correction for technical domains.
Approach A
Automatic
Approach B
human-reviewed captions
Selection considerations
Apply review where broadcast, healthcare, legal, educational, or public content requires it.
Approach A
Centralized
Approach B
edge speech processing
Selection considerations
Choose according to latency, privacy, bandwidth, and device capability.
Approach A
Transcript-only
Approach B
multimodal indexing
Selection considerations
Add slides, OCR, video events, and documents where they materially improve search.
REPRESENTATIVE SCENARIOS
Representative examples: Each scenario preserves timing, speakers, language, review status, and the connection between generated text and source media.
ENGAGEMENT APPROACH
Phase 1
Define sources, languages, terminology, latency, formats, review, search, privacy, and deployment.
Phase 2
Prove quality, timing, speakers, captions, subtitles, translation, and media linkage.
Phase 3
Build STT, media processing, review, localization, search, APIs, applications, and infrastructure.
Phase 4
Validate terminology, latency, scale, corrections, languages, models, failure, and ownership.
POSSIBLE DELIVERABLES
Final deliverables depend on the selected architecture, validation evidence, and engagement scope.
Start with the workflow, evidence, integration, deployment, performance, and operating constraints that determine whether this system can work in production.
START A TECHNICAL CONVERSATION
Share the product, workload, architecture, infrastructure, performance, security, or delivery constraint that must be resolved.
Austin, Texas
Distributed engineering teams across North America, Europe, the Caucasus, and Latin America.
[email protected]