Whisper Speech Recognition

⬢ ティア 2テクニカル

高い

給与インパクト

3か月

習得までの期間

普通

難易度

職種数

概要

Whisper is OpenAI's speech recognition model that transcribes audio in 99 languages with high accuracy. Available as open-source model, API, or fine-tuned versions. Used by developers building transcription apps, accessibility tools, meeting recorders, and voice assistants. Specialists integrate Whisper into applications, optimize for latency/cost, and handle edge cases. Salary band: $115–170k mid-level. 3–4 weeks to baseline; 2+ months for production mastery.

Whisper Speech Recognitionとは

Whisper is OpenAI's open-source speech recognition model that transcribes audio in 99 languages. It's available as an open-source PyTorch model (self-hosted) or via the OpenAI API. Whisper is robust to accents, background noise, and technical language, outperforming many existing speech recognition systems. Use cases: transcription apps, meeting recordings, accessibility (captions for video), voice commands, and voice-based search. Specialists integrate Whisper into applications, optimize for cost/latency, and handle edge cases (noise, multiple speakers, domain-specific language).

🔧 ツール＆エコシステム

OpenAI Whisper APIWhisper Open-Source ModelPython / Node.js SDKsAudio Processing (librosa, pydub)GPU Optimization (CUDA, TensorRT)Streaming Libraries (ffmpeg)React / Frontend IntegrationSupabase / Backend Services

💰 地域別給与

地域	ジュニア	ミドル	シニア
USA	$90k	$150k	$215k
UK	$55k	$95k	$140k
EU	$60k	$105k	$155k
CANADA	$85k	$140k	$200k

🎓 認定資格

OpenAI Whisper API Documentation Speech Recognition Fundamentals

🎯 Whisper Speech Recognitionを使う職種

Voice Ai Engineer

❓ よくある質問

Should I use Whisper API or self-hosted model?

API is easiest (pay per use, no GPU needed). Self-hosted model is cheaper at scale and gives more control. Choose based on volume and latency needs.

What languages does Whisper support?

99 languages. Training data quality varies by language; English and major languages are strongest. Test on your language; quality may vary.

How accurate is Whisper?

Excellent on clear audio (WER ~5-10%). Degrades with background noise, accents, domain-specific jargon. Test on your audio; accuracy depends on audio quality.

Can I fine-tune Whisper?

Yes, the open-source model can be fine-tuned on domain data. API doesn't support fine-tuning yet. Self-hosted fine-tuning requires GPU and ML expertise.

What's the latency for transcription?

API: 5-30s depending on audio length and load. Self-hosted: 2-10s on GPU. Real-time streaming with latency compensation is possible with advanced techniques.

このスキルが自分に合うか迷っていますか？

キャリアマッチを受ければ、適したトラックをご提案します。

自分に合うスキルを見つける →

理想のキャリアパスを見つけよう

2,536件の職種を対象にしたスキルベースマッチング。無料、約2分。

キャリアマッチを受ける（無料）→

全スキル