| Troubleshooting | L37-L47 | Diagnosing and fixing common Azure Speech/Text-to-Speech/Voice Live API and SDK errors, container and Foundry issues, CRL/compatibility problems, and retrieving session/transcription IDs for support. |
| Best Practices | L48-L64 | Best practices for audio/video prep, custom voice/avatars, latency and memory tuning, phrase/keyword optimization, and handling real-time Voice Live interactions and interruptions |
| Decision Making | L65-L82 | Guidance on choosing speech features (batch STT, custom/embedded/personal/Whisper), evaluating models/devices, and step‑by‑step migration between Speech API versions and services |
| Architecture & Design Patterns | L83-L87 | Architectural guidance for building call center voice agents using Azure AI Speech with Voice Live and Azure Communication Services, including integration patterns and design best practices. |
| Limits & Quotas | L88-L96 | Quotas, limits, and usage patterns for Azure Speech: batch TTS, custom/pro voice training & deployment, and short audio STT, plus throttling and capacity planning guidance. |
| Security | L97-L108 | Configuring security for Azure AI Speech: auth (Entra, RBAC), network isolation (VNet, Private Link, sovereign clouds), BYOS storage, encryption/keys, and voice talent consent management. |
| Configuration | L109-L143 | Configuring Azure AI Speech/Voice: audio inputs, logging, storage, SSML, languages/voices, custom speech & voice training, batch/real-time settings, and Voice Live/avatars options. |
| Integrations & Coding Patterns | L144-L168 | Patterns and APIs for integrating Azure Speech into apps and voice agents: telephony, SDK/REST, TTS/avatars, translation, OpenAI/Foundry, Voice Live, consent, and automation workflows. |
| Deployment | L169-L180 | Deploying and scaling Azure AI Speech: Docker/Kubernetes containers, on-prem STT/TTS, custom speech models/endpoints, language ID, and batch/long-form synthesis workflows. |