# Tools

> Every listed resource, editors’ picks first. The filters below can be combined.

- Search: append `?q=<keywords>` to the URL. Separate several keywords with spaces; all of them must match. Matches name, repository, tags, professions, description and README.
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Tagged `python`, `speech`: 7 items.

- [WhisperX](https://hebbmind.com/es/cli/whisperx.md): [CLI] Fast speech transcription built on faster-whisper, with word-level timestamps and speaker diarization, suited to meeting notes and subtitles. Diarization needs a Hugging Face token; GPU acceleration needs CUDA.
- [FunASR](https://hebbmind.com/es/cli/funasr.md): [CLI] Industrial-grade open-source speech recognition toolkit from Alibaba's ModelScope, with an agent-friendly funasr command that turns audio into text, JSON or SRT subtitles in one step, with speaker diarization and timestamps. Strong on Chinese. Requires PyTorch.
- [notebooklm-py](https://hebbmind.com/es/cli/notebooklm-py.md): [CLI] Unofficial Python library and CLI for driving Google NotebookLM (now Gemini Notebook): bulk-import sources, ask cited questions, and generate and download podcasts, videos, slides, quizzes and flashcards. Ships an agent skill. Relies on undocumented APIs and needs a Google sign-in.
- [edge-tts](https://hebbmind.com/es/cli/edge-tts.md): [CLI] Converts text to speech with Microsoft Edge's online TTS service and can generate subtitle files at the same time. No API key needed, with voices for many languages. Not an official Microsoft project and depends on that online service staying available.
- [MLX-Audio](https://hebbmind.com/es/cli/mlx-audio.md): [CLI] Offline speech toolkit for Apple Silicon Macs: CLI text-to-speech (including Chinese and voice cloning) and speech-to-text, for voicing lessons and explainer videos or transcribing lectures and interviews, with data staying local. Needs an M-series Mac and Python 3.10+; MP3 export needs ffmpeg.
- [VoiceMode](https://hebbmind.com/es/mcp/voicemode.md): [MCP] Adds voice conversations to Claude Code and other agents: speak, and it detects silence, transcribes, and reads replies aloud. Runs offline with local Whisper and Kokoro, or uses OpenAI's speech APIs; needs a microphone and speakers.
- [whisper-ctranslate2](https://hebbmind.com/es/cli/whisper-ctranslate2.md): [CLI] Local transcription that's compatible with the OpenAI Whisper CLI but faster and lighter: outputs SRT/VTT subtitles or text and can transcribe a live microphone. Needs Python; models download on first run; speaker labels need pyannote.audio and a Hugging Face token.