Skill UI

A comprehensive Java SDK for building robust, server-side call automation workflows using Azure Communication Services (ACS). It allows developers to implement sophisticated IVR systems, dynamic call routing, interactive media playback (Text-to-Speech, audio files), speech and DTMF recognition, call recording management, and participant handling. Ideal for building sophisticated customer service bots or automated notification systems.

A comprehensive Java SDK for building robust, server-side call automation workflows using Azure Communication Services (ACS). It allows developers to implement sophisticated IVR systems, dynamic call routing, interactive media playback (Text-to-Speech, audio files), speech and DTMF recognition, call recording management, and participant handling. Ideal for building sophisticated customer service bots or automated notification systems.

A comprehensive guide for diagnosing and fixing common Deepgram API errors. Covers HTTP error codes, WebSocket issues, optimal audio preparation using ffmpeg, and implementing robust retry patterns for reliable Speech-to-Text integration.

A comprehensive workflow for production-grade, pre-recorded Speech-to-Text (STT) transcription using the Deepgram API. This skill supports transcribing audio from URLs or local files, offering advanced features such as speaker diarization, automatic summaries, sentiment analysis, and topic detection. It also includes robust batch processing methods for handling large datasets.

This guide provides minimal working examples for Deepgram speech-to-text transcription. It demonstrates how to transcribe audio from a URL or a local file using both TypeScript and Python. Users can learn basic API patterns, implement advanced features like diarization (speaker identification), and compare various model options (e.g., nova-3, nova-2). Ideal for initial integration and testing.

Provides production-ready coding patterns for integrating Deepgram using TypeScript and Python. This guide covers essential best practices, including implementing singleton client management, performing text-to-speech synthesis with Aura, and setting up advanced audio intelligence pipelines (e.g., summarization, topic detection, sentiment analysis). Use this when establishing robust Deepgram integration standards, refactoring existing SDK usage, or migrating to newer SDK versions.

Process videos, audio, images, and documents on Transloadit’s cloud using 86+ robots to encode formats, generate thumbnails, resize/watermark, run OCR, speech-to-text, moderation, and chain multi-step pipelines for scalable media automation.

This skill provides a comprehensive guide to optimizing costs when using AssemblyAI for speech-to-text transcription. It details model selection (Best vs. Nano), guides feature budgeting (e.g., Diarization, Sentiment Analysis), and includes code examples for cost estimation and usage tracking. Use this when managing billing, reducing operational expenses, or implementing budget alerts for high-volume audio processing.

A comprehensive, production-ready reference architecture for building robust, scalable transcription services using AssemblyAI. This guide demonstrates best practices for layered system design, covering API endpoints, service logic, client management, and infrastructure integration (webhooks, database). It is ideal for designing new high-throughput speech-to-text applications.

This guide demonstrates how to set up robust Continuous Integration/Continuous Deployment (CI/CD) pipelines for projects utilizing AssemblyAI's speech-to-text services. It provides detailed GitHub Actions workflows for running both mocked unit tests (free and fast) and live, cost-controlled integration tests. Learn how to safely manage API keys and ensure transcription stability in your automated build process.

Collects comprehensive diagnostic evidence for support tickets related to AssemblyAI. This utility automates the gathering of runtime environment details, SDK versions, API connectivity checks, and specific transcript statuses, greatly accelerating troubleshooting and issue resolution for speech-to-text applications.

This comprehensive checklist guides the secure and robust deployment of AssemblyAI transcription services to a live production environment. It covers critical pre-deployment checks, health monitoring implementations, webhook-based processing setup, and gradual rollout strategies, ensuring high availability and reliability for mission-critical speech-to-text functions.