'transcription' 검색 결과

Use Azure's Python transcription client to turn audio files into text and review timestamped results. Covers authentication, installed SDK options, and error handling, while clarifying when streaming or asynchronous batch work needs a different Speech API.

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• Transcribe a local recording with consent
• Review timestamped transcription output
• Check authentication and installed SDK options

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization. Triggers: "transcription", "speech to text", "Azure AI Transcription", "TranscriptionClient".

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Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization. Triggers: "transcription", "speech to text", "Azure AI Transcription", "TranscriptionClient".

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Build transcription workflows for uploaded or stored audio and video using Zoom AI Services Scribe. Consult guidance on authentication, single-file requests, batch jobs, completion notifications, and saving transcript results for further processing.

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• Adding transcription for uploaded recordings
• Transcribing stored call archives in batches
• Saving transcripts after job completion notifications

Turn audio and video into text with Whisper, including Japanese and other supported languages. This skill covers transcription, English translation, timestamped subtitles, model selection, and batch processing, with guidance on hardware needs and recognition limitations.

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• Transcribing recorded meetings
• Creating subtitles for videos
• Translating multilingual recordings into English text

Turn recorded audio and video into text or timestamped subtitles with Whisper. This skill covers transcription across 99 languages, language detection, translation into English, batch processing, and model selection for available computing resources.

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• Transcribe recorded meetings
• Turn podcasts into text
• Generate SRT or VTT subtitles for videos

Ultra-fast speech transcription using iFLYTEK Speed Transcription API. Transcribe audio files (WAV/PCM/MP3) up to 5 hours in ~20 seconds per hour. Supports Chinese, English, and 202+ Chinese dialects with automatic language detection. Use when user asks to transcribe audio files, convert speech to text, or mentions "speed transcription" or "极速转写".

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Build audio transcription pipelines with Whisper, Deepgram, and AssemblyAI including speaker diarization and real-time streaming. Activate on: transcription, speech-to-text, diarization, audio processing, meeting transcripts. NOT for: text-to-speech synthesis (voice-audio-engineer), music generation (ai-engineer).

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Build audio transcription pipelines with Whisper, Deepgram, and AssemblyAI including speaker diarization and real-time streaming. Activate on: transcription, speech-to-text, diarization, audio processing, meeting transcripts. NOT for: text-to-speech synthesis (voice-audio-engineer), music generation (ai-engineer).

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음성 파일을 OpenAI 전사 API로 보내 결과를 텍스트나 JSON으로 저장합니다. 모델과 언어를 지정하고 화자별로 발언을 구분할 수 있습니다.

• 회의 녹음을 텍스트로 변환합니다
• 인터뷰에서 화자를 구분합니다
• 전사 결과를 JSON으로 저장합니다

Venice.ai API를 사용하는 영상 생성과 전사 작업을 안내합니다. 전체 절차를 실행하려면 제공처의 스크립트, 자료, 참고 문서가 포함된 묶음을 별도로 설치해야 합니다.

• Venice.ai API로 영상 생성
• Venice.ai를 통한 전사 작업
• 에이전트의 영상 관련 작업 계획

Transcribe audio with Azure AI Speech and obtain word timestamps, speaker labels, and language identification. Use the resulting transcript in OpenMontage subtitle workflows, with a compatible local transcription fallback when Azure is unavailable.

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• Transcribing recorded audio
• Preparing timestamps for video subtitles
• Labeling speakers in interviews

Help implement Azure OpenAI features in C# and .NET applications using SDK examples. Cover authentication, chat, document-backed answers, image generation, and audio processing, including transcription and speech generation.

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• Adding streaming chat to a .NET application
• Generating JSON responses in a defined format
• Building answers backed by Azure AI Search

Develop C++ bots that join existing Zoom meetings from Linux servers without a graphical interface. Follow guidance for recording raw audio and video, feeding transcription or AI workflows, and handling authentication, recording permissions, and Docker audio setup.

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• Build a bot that automatically joins and records Zoom meetings
• Feed meeting audio into a transcription service
• Connect transcripts to AI summaries and action item extraction

Use Screenpipe’s local REST API, an interface for programmatic requests, to search screen and meeting history, review app activity and active time, retrieve synced-device records, export recordings, and rerun audio transcription.

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• Reviewing daily app use and active screen time
• Finding decisions in recorded meetings
• Searching history from a synced device

Plan interviews and focus groups for qualitative research, which explores people’s experiences and views. Develop question guides, follow-up prompts, discussion plans, transcription conventions, and participant review procedures suited to the study.

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• Preparing a semi-structured interview guide
• Planning focus group discussions
• Choosing transcription conventions

Build applications that exchange live audio, video, and text with the Gemini Live API. Covers voice conversations, streaming transcription and translation, session recovery, authentication, and migration from older Live models in Python or JavaScript/TypeScript.

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• Build an AI app for live voice conversations
• Add real-time transcription or speech translation
• Send camera or screen frames alongside audio

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. Triggers: "speech to text REST", "short audio transcription", "speech recognition REST API", "STT REST", "recognize speech REST". DO NOT USE FOR: Long audio (>60 seconds), real-time streaming, batch transcription, custom speech models, speech translation. Use Speech SDK or Batch Transcription API instead.

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Use when analyzing transcription factor (TF) regulatory networks using Dorothea database. Input gene list, identify regulating transcription factors, generate TF-Target network visualization. For: transcription factor enrichment analysis, gene regulatory network research.

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Analyze, summarize, and extract insights from DeLive transcription sessions. Use when: user mentions DeLive, transcription, meeting transcripts, live captions, audio transcription, AI correction, corrected transcript, or transcript analysis; user wants to search, retrieve, summarize, correct, or process recorded transcripts; user asks about meeting notes, action items, discussion summaries, or transcript quality from DeLive. Requires DeLive app running locally with its MCP server or REST API.

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Inspect and manually purge the Soniox artifacts — transcriptions and uploaded audio files — that offline transcription leaves behind, on dev or prod. Use when offline transcription silently stops working, when Soniox answers 429 `limit_exceeded`, when `SonioxTranscriberTest.OfflineTranscribeWorks` and `CleanerDeletesEnqueuedArtifacts` fail together, or when the user says "sweep Soniox", "soniox/sonoix sweep", "sonoix swipe", "purge Soniox", "check Soniox files", or "is Soniox at the cap".

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Select an OCR/HTR engine by benchmarking candidates on the same labelled samples — source ground truth from open datasets (e.g. Hugging Face PAGE-XML corpora) or hand-transcription, wrap every engine behind a transcribe(image_path) -> str adapter (vision-LLMs via any OpenAI-compatible endpoint, dedicated HTR REST APIs, cloud OCR), and score with zero-dependency raw CER, lenient CER, WER, and a critical name/date token diff. Use when choosing an engine for handwriting or historical-document transcription, when published accuracy claims need honest verification on your own material, or when a records workflow must surface confident-but-wrong names and dates that a low aggregate CER hides.

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Rewrite raw meeting audio transcriptions into clean, accurate meeting minutes in Traditional Chinese. Use when the user has an unprocessed audio transcription file with recognition errors and needs it cleaned up into proper meeting minutes.

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Use this skill when setting up Service Cloud Voice with Amazon Connect — provisioning the contact center, configuring phone numbers, enabling real-time transcription, and configuring After Conversation Work Time. Covers the deployable metadata behind it: CallCenter, ConversationVendorInfo (vendorType), CallCenterRoutingMap, the Voice ServiceChannel that carries ACW, ServicePresenceStatus, PresenceUserConfig, ServiceCloudVoice.settings, and the VoiceCall / VoiceCallRecording objects. Trigger keywords: Service Cloud Voice, Amazon Connect, contact center, softphone, call transcription, After Conversation Work, ACW, wrap-up time, VoiceCall, CallCenter metadata, vendorType, telephony provider. NOT for Omni-Channel routing setup — use admin/omni-channel-routing-setup. NOT for Open CTI softphone adapters — use apex/cti-adapter-development. NOT for Sales Dialer (Voice.settings) — that is a different product.

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