Build text translation, speech interpretation, STT, and TTS as individual modules or connect them to live captions and translated voice in video conversations. Design language pairs, domain terminology, conversational latency, and data handling together.
Build text translation, speech translation, STT, or TTS independently, or integrate them into video conversations. Scope language support and delivery around the actual operating environment.
Build translation APIs and review interfaces for documents, chat, product content, and support. Manage terminology, register, named entities, and number formatting by language pair. Link translated segments to their source and preserve review and revision history.
Turn microphone or file audio into translated captions and synthesized speech. Compare an STT → translation → TTS pipeline with direct speech-translation models against the task. Handle utterance boundaries and revisions to intermediate results explicitly.
Build transcription APIs, tools, and live captions without a translation stage. Define sample-rate and channel normalization, partial versus final results, segment timestamps, and optional speaker diarization. Separating speakers is distinct from identifying who they are.
Build speech-generation APIs and playback from source or translated text. Validate provider-specific SSML support, pronunciation dictionaries, number reading, speaking rate, and chunked playback. Cancel queued audio when the text changes or playback is interrupted.
Connect per-participant language selection, original and translated captions, and optional translated voice to browser or app video calls. Separate the call from translation processing to handle delayed captions, mute, reconnects, and overlapping speech. Design playback routing to avoid feeding translated audio back into recognition.
Speech passes through recognition, translation, and synthesis. Text can enter translation or TTS directly, while transcripts and translated captions are separate outputs. Video conversations connect each participant’s audio to the same processing flow.
Scroll the diagram horizontally to inspect the complete flow
Concrete design decisions and acceptance scenarios to agree for the project.
ImplementationLanguage pairs, glossary, voice, source preservation, review criteria
ValidationEvaluate names, numbers, noise, accents, and language switches
ImplementationSegment IDs, partial/final states, caption timing, cancellation, backpressure
ValidationRevised transcripts, overlapping speech, slow consumers, reconnects
ImplementationAPI or private deployment, concurrency, audio/transcript retention, access
ValidationOriginal-call behavior during translation failure, session cancellation, deletion
Technology choices and acceptance criteria depend on discovery, integrations, and agreed scope. We define reproducible acceptance scenarios and handover evidence for the operating environment.
From visible features to failure conditions,
we work through the decisions before launch.
Select models using the actual language pairs and representative documents or conversations. Specify glossary versions, protected strings, number and unit preservation, and context windows. Combine automated evaluation with human review of meaning and terminology. Apply masking and access rules before external API calls; track source revisions so only affected segments need reprocessing.
Distinguish voice activity, end-of-utterance detection, and partial versus final recognition. Link source segments, translations, and audio chunks through session, utterance, and segment IDs. Update revised captions without replaying committed speech. Standalone STT preserves timestamp and ordering contracts; standalone TTS validates locale, voice, codec, pronunciation, cancellation, and playback-queue behavior.
Define participant and track management, signaling, ICE connectivity, and TURN relay requirements. For group calls, assess an SFU or media server and per-participant audio processing. Caption events carry speaker, language, and segment timing. Keep the original call state distinct from translation availability, and reject stale results after mute, device changes, reconnects, or session cancellation.
Evaluate STT with fixed language-specific normalization and tokenization for WER/CER, plus domain-term recognition. Review translation for meaning, numbers, and terminology, and TTS for pronunciation, continuity, and intelligibility. Measure p50/p95 time from utterance end to committed captions and first translated audio, separately from queue delay. Choose API or private deployment against model, language, and concurrency requirements, with explicit recording, transcript-access, and deletion policies.
Understand your goals, workflows, and operating environment.
Define features, priorities, and integration requirements.
Build the agreed scope and review progress together.
Prepare testing, deployment, and operational handover.
You don’t need a finished specification.
Start with the problem you want to solve.
