「speech」の検索結果

Add or revise scene-bound narration or speech-linked captions in the active iPolloWork video using actual voice settings, measured audio and alignment.

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Draws original design-and-coding scenes as SVG cards (480x360) in a framed-panel cartoon style. Identifying traits are a soft pastel card with a periwinkle-violet panel framed in thin navy, outline-only clouds and a pale lavender floor band with dashes inside it; L-shaped corner brackets outside two corners; white speech bubbles, UI cards and bushes that break out over the frame edge; and a semi-real character with a thin navy outline (1.25 px), muted flat fills, navy hair with violet highlights, blush and short paired hatch marks. Covers people working with laptops, screens, UI parts and devices. Use when someone asks for a framed panel, window-frame or picture-frame illustration, pastel violet cartoon, outlined flat character scene, empty-state, onboarding or 404 art, a blog header, a feature spot, a support, about or team page illustration, or a marketing card with a person.

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0G Compute Network guide for decentralized AI inference, fine-tuning, and GPU services. Covers chatbots, image generation, speech-to-text, SDK integration (0g-serving-broker), processResponse API, broker.inference methods, CLI commands (0g-compute-cli), and account management. Use this skill for any 0G compute, 0G AI, or decentralized GPU question.

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Use DeepChat's bundled CLI control plane for model inference, image/video/speech generation, transcription, OCR, artifact inspection, public configuration, Skills, and MCP operations. Activate when a user asks to invoke DeepChat capabilities that are not already exposed as a more specific tool, compare models, run a benchmark, inspect DeepChat runtime state, or manage DeepChat through the CLI.

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Transform verbose voice input into structured, token-efficient Claude prompts. Use when cleaning up voice memos, dictation output, or speech-to-text transcriptions that contain filler words, repetitions, and unstructured thoughts.

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Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, speech generation (TTS), voice design, voice replication, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. Covers SDK usage and best practices for Gemini models and agents in Python and TypeScript.

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Local speech-to-text with the Whisper CLI (no API key).

日本語の概要は準備中です。原文の説明を表示しています。

Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.

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This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.

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Voice operations — make phone calls (Bland AI), text-to-speech (ElevenLabs), transcribe audio (Whisper/Groq). Replace OpenClaw voice capabilities.

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视频转文字。用户发抖音分享链接（获取标题/作者/点赞等元数据），或本地视频文件（语音转写全文）时使用。抖音链接用 SSR 解析无需 Cookie。Video to text: extract metadata from Douyin share links, or transcribe speech from local video files.

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Integrate and route AI model requests through RouterBase. Use when migrating OpenAI-compatible clients, choosing model IDs, configuring fallbacks, or building chat, image, video, audio, speech, and embedding workflows.

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【WORKFLOW SKILL】根据输入视频的音频信息进行口播粗剪。Rough cut based on audio information from the input video for narration.

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Analyze text and images for harmful content using Azure AI Content Safety (@azure-rest/ai-content-safety). Use when moderating user-generated content, detecting hate speech, violence, sexual content, or self-harm, or managing custom blocklists.

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Build call automation workflows with Azure Communication Services Call Automation Java SDK. Use when implementing IVR systems, call routing, call recording, DTMF recognition, text-to-speech, or AI-powered call flows.

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Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.

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Analyze and apply AssemblyAI secret, region, consent, retention, deletion, and model-training controls. Use when reviewing security or regulated speech workflows. Trigger with "AssemblyAI security", "AssemblyAI privacy", or "data retention".

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Analyze and operate a production AssemblyAI pre-recorded pipeline with explicit models, Speech Understanding, callbacks, and retention controls. Use when running asynchronous transcription. Trigger with "AssemblyAI async transcription" or "pre-recorded pipeline".

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Local speech-to-text transcription on Apple Silicon macOS. Supports wav directly and other audio formats via ffmpeg.

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Generate audio narration of blog posts using Google Gemini TTS. Supports summary narration, full article read-aloud, and two-speaker podcast/dialogue mode with 30 voice options. Outputs MP3 with HTML5 audio embed code. Works standalone via /blog audio or internally from blog-write. Falls back gracefully when API key is not configured. Use when user says "blog audio", "narrate blog", "audio version", "text to speech", "tts", "podcast mode", "read aloud", "audio narration", "voice", "narration", "generate audio".

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Use when a video/audio task needs OpenChatCut transcription, captions, subtitles, subtitle styling, transcript search, transcript readiness checks, or enabling captions, including local or attached videos where the user asks to add captions/subtitles, transcribe, create bilingual subtitles, clean talking-head speech, remove filler words, or trim pauses.

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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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Practical mastering steps for TTS audio: cleanup, loudness normalization, alignment, and delivery specs.

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Transcribe video to timestamped text using Whisper tiny model (pre-installed).

日本語の概要は準備中です。原文の説明を表示しています。