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How to transcribe long Japanese recordings with timestamps with Speech CPP

Turn a Japanese meeting or interview recording into punctuated text with times, on your own machine.

Authorization notice. Speech CPP is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.

Remote script. The install step runs a shell or PowerShell script fetched from the internet, so read it first if your policy requires it.

Who it is forA researcher, journalist or team member with long Japanese audio recordings who needs a searchable transcript without uploading the files to a cloud service.

The problemLong Japanese recordings are slow to type up by hand, and cloud transcription may not suit private material.

The outcomeA text transcript of the recording with timestamps, produced locally by the reazonspeech-v2 model.

What you need first

  • macOS on Apple silicon, Linux on x86-64, or Windows x64
  • Internet access to fetch the installer and models from Hugging Face the first time
  • Free disk space for the model files, for example 1.21 GB for qwen3-tts-0.6b
  • A terminal (PowerShell on Windows)
  • A microphone, for live transcription

Steps

  1. Install speech with curl -fsSL https://raw.githubusercontent.com/nyosegawa/speech.cpp/main/install.sh | sh on macOS or Linux, or irm https://raw.githubusercontent.com/nyosegawa/speech.cpp/main/install.ps1 | iex in PowerShell on Windows.
  2. Put the recording in a WAVE file, for example meeting.wav.
  3. Run speech asr reazonspeech-v2 --timestamps meeting.wav. The model is fetched the first time.
  4. Check the first few lines of the output against the audio, since the model is for Japanese only.

Prompt for your agent

Using the speech.cpp repo (nyosegawa/speech.cpp), install the speech command, then run `speech asr reazonspeech-v2 --timestamps <path-to-wav>` on the target WAVE file. Expected output: Japanese text with timestamps printed to the terminal. Verify that the first line matches the opening words of the audio.

Caveat. The reazonspeech-v2 model in the README is listed for Japanese only, so use qwen3-asr or parakeet models for other languages.

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