Results for “stt”
9 skills
whd4 Voice Agents
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
0
danstrem2 Voice Agents
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
2
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cloudthinker-ai Managing Sst
Manages SST applications by discovering project config, checking stack status, and inspecting bound resources. Supports deployment, live Lambda debugging, secret management, and multi-stage environments.
7
openai Sentry
Inspect Sentry issues, events, and production errors using the Sentry CLI for read-only observability queries.
23.3k · bundle
mukul975 Integrating Sast Into Github Actions Pipeline
Integrates Static Application Security Testing (SAST) tools—CodeQL and Semgrep—into GitHub Actions CI/CD pipelines, configuring automated code scanning, tuning rules, uploading SARIF results, and establishing quality gates that block merges on high-severity vulnerabilities.
24.6k · bundle
chimeranext Static Analysis
Configures and runs static analysis and linting tools across multiple languages, integrating with CI/CD and security platforms.
4
dokhacgiakhoa Voice Agents
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
505 · bundle
tinh2 Secure
Performs a full-stack security posture assessment with 0-100 risk scoring, scanning dependencies, code patterns, configuration, and data handling, then produces a prioritized report and routes to specialized skills.
13
atc-net Azure Speech
Expert knowledge for Azure AI Speech development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using STT/TTS APIs, custom voice/avatars, Voice Live, batch transcription, or containerized speech services, and other Azure AI Speech related development tasks. Not for Azure Communication Services (use azure-communication-services), Azure AI Bot Service (use azure-bot-service), Azure AI Video Indexer (use azure-video-indexer), Azure AI Immersive Reader (use azure-immersive-reader).
3