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Found 20 Skills
Transcribe speech to text using the Speech framework. Use when implementing live microphone transcription with AVAudioEngine, recognizing pre-recorded audio files, configuring on-device vs server-based recognition, handling authorization flows, or adopting the new SpeechAnalyzer API (iOS 26+) for modern async/await speech-to-text.
Fully offline speech-to-text via the Vosk library — streaming recognition, 16 kHz PCM, no network required after model download.
Implement speech-to-text voice input in Blazor applications using Syncfusion SpeechToText component. ALWAYS use this when users need voice input, speech recognition, audio transcription, or implementing the SpeechToText component in Blazor. Trigger for Syncfusion.Blazor.Inputs, microphone input, voice-to-text conversion, language support, transcript binding, listening states, error handling, browser speech API, or any speech recognition requirements.
Configure Tavus CVI personas with custom LLMs, TTS engines, perception, and turn-taking. Use when customizing AI behavior, bringing your own LLM, configuring voice/TTS, enabling vision with Raven, or tuning conversation flow with Sparrow.
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.
Implement the Syncfusion Angular SpeechToText component. Use this skill for real-time speech-to-text conversion with text transcripts, custom button appearance and tooltips, recognition event handling, multiple language support with localization and RTL, error handling, and security best practices for microphone access and data transmission.
DashScope (Alibaba Cloud Bailian / 阿里云百炼) integration — image generation (qwen-image-2.0-pro), text-to-speech (qwen3-tts-flash), and ASR with word-level timestamps (qwen3-asr-flash-filetrans). Use when generating images via Qwen-Image, narrating via Qwen-TTS, or transcribing with word-level timestamps via Qwen-ASR.
Transcribe audio files to text using local speech recognition. Triggers on: "转录", "transcribe", "语音转文字", "ASR", "识别音频", "把这段音频转成文字".
Stage 1 of Clinical ASR Flywheel. Use when bootstrapping a cycle: NVCF+MW disclosure, NVIDIA_API_KEY check, deps install, TTS+ASR smoke test.
Correct subtitle files (.srt) generated from speech recognition. Use when the user uploads subtitle files and asks to correct, fix, or proofread subtitles, especially for technical content like programming tutorials, AI/ML courses, or any content with domain-specific terminology. Supports Chinese and English subtitles with intelligent error detection and correction while preserving exact timeline information.
Video understanding and transcription with intelligent multi-provider fallback. Use when: (1) Transcribing video or audio content, (2) Understanding video content including visual elements and scenes, (3) Analyzing YouTube videos by URL, (4) Extracting information from local video files, (5) Getting timestamps, summaries, or answering questions about video content. Automatically selects the best available provider based on configured API keys - prefers full video understanding (Gemini/OpenRouter) over ASR-only providers. Supports model selection per provider.
ASR (Automatic Speech Recognition) — enhanced speech-to-text built on Doubao large model, with audio preprocessing, denoising, and extended analysis capabilities. Async API. Choose this skill when: - Input is a video file (mp4/mov/mkv) — auto-extracts audio track - Audio needs denoising before recognition - File exceeds 512MB or 5 hours (no size limit) - Audio source is a TOS internal path (tos://bucket/key) - Need structured JSON output with timestamped utterances and metadata - Need speaker diarization, emotion/gender detection, speech rate, or sensitive word filtering Supports 99 languages, multiple formats (wav/mp3/m4a/aac/flac/ogg/mp4/mov/mkv), and auto language detection.