Post-Stream Refinement (PSR) for Azure AI Speech has reached general availability (GA), offering highly accurate final transcripts without sacrificing instant streaming results. This technology operates by running a second recognition pass in parallel with streaming, replacing initial segments with more accurate versions upon utterance completion. The GA release introduces crucial production capabilities, including diarization for speaker attribution, phrase lists for domain-specific vocabulary, and expanded support to 19 locales across 22 Azure regions. Existing real-time contracts and partial-result streaming remain unchanged; users simply enable refinement by setting a property on their SpeechConfig.Diarization support in PSR ensures that speaker labels are preserved in the refined transcript, making it ideal for meetings, contact centers, and interviews. Phrase lists allow the recognizer to prioritize specific terms, significantly improving accuracy for product names and specialized vocabulary. Internal testing has shown double-digit relative reductions in word error rate, particularly for long utterances and proper nouns. While partial-result latency is unaffected, the final segment may experience a slight increase due to refinement.PSR is now available in 19 locales, including several Indic languages, and across 22 Azure regions in the Americas, Europe, and Asia Pacific. This technology, already powering Microsoft Teams and Microsoft 365 Copilot, brings a production-grade transcription experience to Azure AI Speech customers. To get started, users need Speech SDK 1.50 or later, a Speech resource in a supported region, and the session locale set on the recognizer.A 'PostRefinement' option needs to be set in the SpeechConfig, and optional phrase lists can be added. For scenarios involving multiple languages or code-switching, a Multilingual PSR public preview is available. However, for a known session locale with phrase lists and diarization, the Monolingual GA path is recommended. This release offers a significant leap in transcription quality for Azure AI Speech applications with a minimal configuration change.