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Use for Deepgram speech and voice production workflows: speech-to-text transcription, live captions, diarization, audio intelligence, Aura text-to-speech, Flux and Voice Agent live audio, model selection, cost/limits/privacy checks, artifact custody, and production QA.
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Internal speech module for /codeck. Reads deck content, asks about style and duration only when missing, generates a verbatim speech transcript with stage directions. Outputs $DECK_DIR/speech.md.
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Transcribes and analyzes speech with the Deepgram API: pre-recorded audio, real-time streaming, text-to-speech and voice agents. Use when a user asks to convert speech to text, implement real-time transcription, add speaker labels or summaries to a recording, detect languages, build a voice agent with turn detection, or integrate Deepgram SDKs (JavaScript or Python).
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Replaces the voice in a video or audio file with one from the Novoads voice catalog, over the REST API. Converts the SPEECH in the source to a voice you pick, keeps the original timing so lip-sync survives, and returns audio that gets muxed back over the untouched picture locally. Casts by MEASURING the source voice against auditioned candidates instead of reading labels, refuses a source with no speech before anything is charged, fences sound effects and music so they survive from the original track, and verifies the finished file by transcribing it. Use when an actor's voice sounds robotic, flat, thin or simply wrong, and for "change the voice", "voice swap", "swap the voice on this ad", "re-voice my ad", "the actor's voice sounds bad", "make him sound human", "different voice for this video", "speech to speech", "same video better voice". Not for narrating a silent clip (that is a voice-over), not translation, and it changes neither pronunciation nor accent.
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Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
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OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
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OpenAI API (developers.openai.com) の音声 API リファレンス。 GPT-Live (gpt-live-1, full-duplex, delegation, /v1/live/sessions), Realtime API (WebRTC / WARP / WebSocket / SIP, sessions / events, client secrets, VAD (server_vad / semantic_vad), tools/MCP), speech-to-speech voice agents, speech-to-text (gpt-transcribe / gpt-live-transcribe), text-to-speech, custom voices, translation。
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Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
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OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
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sherpa-onnx 음성 모델로 컴퓨터에서 글을 낭독 음성으로 변환하고 WAV 파일로 저장합니다. 실행 환경과 모델을 준비하면 클라우드 연결 없이 음성을 생성합니다.
ElevenLabs로 글을 음성으로 바꿔 기기에서 재생하거나 파일로 저장합니다. 목소리를 선택하고 발음과 쉼을 조정하며 지원 모델에서는 속삭임이나 감정도 넣습니다.
Turn audio and video into text across 99 languages, translate speech into English, and create timestamped subtitles. The skill covers model selection, transcription settings, and batch processing for recordings such as meetings and podcasts.
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Turn video speech into subtitles, refine and translate the text, and embed subtitles in the video. Review tools compare subtitles with an approved script and generate a preview frame before final export.
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Use the MiniMax API from the command line to generate chat responses and turn text into speech. Select models and voices, adjust speech settings, and save audio files for further use.
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Create subtitles from video or audio, refine and translate subtitle text, and burn captions into video. Control bilingual layouts and visual styles, including fonts, colors, outlines, and rounded backgrounds, or export subtitle files separately.
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Create talking videos from a portrait or existing video and an audio file, with mouth movements, expressions, and body motion aligned to speech. It supports long videos, replacement audio, and speech generated from text.
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Create narration that fits fixed video segments or a continuous long story using one selected voice. Check speech duration and pauses when local tools are available, and adjust wording through regeneration to meet timing requirements.
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Create, refine, or fix NVIDIA voice agents (Cascaded or Omni) with Pipecat or LiveKit. Use when building, scaffolding, or iterating on a real-time voice-agent pipeline, including speech (ASR/TTS) customization and cloud or local deployment. Not for offline/batch speech-to-text, text-only chat or RAG, or generic Docker or CUDA work unrelated to a voice agent.
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Orchestration skill for NVIDIA Nemotron Speech (Riva) / NeMo ASR domain and language adaptation. Given a goal like "improve/fine-tune ASR for my domain or language", it scopes the task, picks the cheapest sufficient path (word boosting → n-gram LM → fine-tuning), delegates each stage to the right sub-skill (data generation, training, evaluation, deployment), and answers cost/time/data questions along the way.
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Guide for editing videos where the primary content is people talking — talking-head / 口播, interview / 访谈, lecture, tutorial, podcast, course content, and similar talking-driven formats. Use when the user wants speech editing on a talking video (剪口播 / 口播剪辑 / 去口癖 / clean up fillers / smooth speech), motion graphics layered onto talking video (口播加 MG / 加动画), or B-roll on a talking video (加 B-roll / add B-roll). For motion graphics specifically, use this together with the active Motion Graphics skill/workflow available in the current OpenChatCut environment — this skill adds talking-specific guidance (speech-rhythm timing, frame-aware placement, subject/caption protection, placement verification).
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