Desktop app that records your on-screen work session and uses the GitHub Copilot CLI to reconstruct it as an intent + ordered steps, then builds a reusable Skill or Automation for Microsoft Scout, Microsoft Copilot Cowork, or Copilot Studio.
Skill ディレクトリ
AI Agent のための再利用可能な Skill を見つける。
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
検索結果: spoken-digits
英語版ディレクトリCreate a new skill in the current repository. Use when the user wants to create/add a new skill, or mentions creating a skill from scratch. This skill follows the workflow defined in .agents/skills/README.md and helps scaffold, validate, and sync new skills.
Build a reproducible local rough-cut workflow for talking-head or narrated screen-recording videos with transcript review gates.
Unified-Modal Speech-Text Pre-Training for Spoken Language Processing
A Claude Code skill that measures brand visibility in AI-generated answers by running a logged-in browser agent across engines like Google AI Overview, ChatGPT, Claude, Gemini, and Yandex Alice.
A free audio dataset of spoken digits. An audio version of MNIST.
RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.
The ChatGPT/DeepSeek Voice Assistant uses a Raspberry Pi (or desktop) to enable spoken conversation with OpenAI or DeepSeek large language models. This implementation listens to speech, processes the conversation through the OpenAI/DeepSeek service, and responds back. Like Apple Siri, Amazon Alex, Google Nest Home, Mi XiaoAi etc.
Place one CALL-E phone call to get a spoken, code-verified human approval before an agent or a pipeline does something irreversible, such as a production deploy, a database restore, a bulk refund or a migration. Use when the approver is away from a keyboard and the action cannot be undone.
Conduct phone-based accessibility intake interviews for users who cannot complete web-based accessibility audit forms (screen reader fatigue, motor impairment, low vision, cognitive load), and produce a structured result mapped to VPAT 2.4 / Section 508 conformance reporting fields.
Place a one-off welcome and onboarding call to a customer who just signed up, capture a structured result such as business type, goal, pain points, sentiment, and activation status, then write that result back to a CRM and queue a human follow-up task when the customer asks for one.
Place one consent-first CALL-E callback after a local safety gate has already blocked an extreme-risk developer action, so a known project owner can say stop or request normal review without granting the agent destructive permission.