# 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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Resources for ML / AI or Research / Academia, Tagged `python`, `speech`: 5 items.

> - ML / AI: Model training, evaluation and LLM application development.
> - Research / Academia: Literature search and reviews, experimental data analysis, paper writing and submission.

- [WhisperX](https://hebbmind.com/ru/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/ru/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/ru/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.
- [MLX-Audio](https://hebbmind.com/ru/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.
- [whisper-ctranslate2](https://hebbmind.com/ru/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.