Train custom wake words in seconds.
Porcupine Wake Word is not just a wake word detection engine, it is “the one”.
- Hot Pink
- Lime Green
- Deep Sky Blue
- Knallpink
- Limettengrün
- Himmelblau
- Rosado Fuerte
- Lima Verde
- Celeste Profundo
- Rose Vif
- Vert Citron
- Bleu Ciel Foncé
- Rosa Caldo
- Verde Lime
- Azzurro
- 桃色
- 萌黄
- 空色
- 핫 핑크
- 라임 그린
- 깊은 하늘색
- Rosa Choque
- Verde Limão
- Azul Celeste
Picovoice is a leader in the field of wake word detection. We are extremely impressed with how easy it is to get a wake word and how well it performs. We have tried other alternatives, but they do not perform as well.
What is Porcupine Wake Word?
Porcupine Wake Word is a wake word detection engine that recognizes unique signals to transition software from passive to active listening.
Porcupine Wake Word enables enterprises to offer hands-free experiences by training and deploying custom wake words like Big Tech - but with superior technology.
Deploy custom wake words with a few lines of code
o = pvporcupine.create(access_key=access_key,keyword_paths=keyword_paths)while True:keyword_index =o.process(audio_frame())if keyword_index >= 0:// Detection callback
Why Porcupine Wake Word?
“Hey Siri”, “Alexa”, and “OK Google” are the most widely known wake words because Big Tech forces enterprises to use only their branded wake words. Legacy vendors hide their old technology behind “talk to sales” and offer mediocre custom wake words only after months of engagements and iteration.
Porcupine Wake Word is what a wake word detection engine should be: lightweight, accurate, and production ready.
Pioneering Wake Word Detection
Porcupine Wake Word always uses the latest inventions of Picovoice researchers
Other Engines
- 🎈“Award-winning”, “Highest accuracy”
- ⏳Delivered in “just a few weeks”
- ⚙️Hardware-centric
- 🏭Vendor-dependent
- 💰“Low-cost” wake word for a PoC
Porcupine Wake Word
- 🔬Scientifically-proven accuracy
- 🚀Ready in Seconds
- 🤸Platform-agnostic
- 👨💻Developer-first
- 💪Free Plan for a PoC
Highly accurate — backed by open-source benchmark, not PowerPoint
Train custom wake words, instantly
Create a Unified Voice Experience Anywhere
Scale globally
- Hot Pink
- Lime Green
- Deep Sky Blue
- Knallpink
- Limettengrün
- Himmelblau
- Rosado Fuerte
- Lima Verde
- Celeste Profundo
- Rose Vif
- Vert Citron
- Bleu Ciel Foncé
- Rosa Caldo
- Verde Lime
- Azzurro
- 桃色
- 萌黄
- 空色
- 핫 핑크
- 라임 그린
- 깊은 하늘색
- Rosa Choque
- Verde Limão
- Azul Celeste
Focus on building, iterating, and improving your product.
Porcupine Wake Word
Does Porcupine Wake Word sound too good to be true? See for yourself!
Start Now- Custom Wake Words
- Platform-optimized model training
- Intuitive SDKs
- Unlimited interactions
- Arabic, Dutch, English, Farsi, French, German, Hindi, Italian, Japanese, Korean, Mandarin, Polish, Portuguese, Russian, Spanish, Swedish, and Vietnamese
Porcupine Wake Word
What is a Wake Word, Trigger Word, or Hotword?
A wake word is a unique phrase that activates dormant applications. For example, Amazon, Apple, and Google devices wake up when they detect Alexa, Hey Siri, and OK Google. Wake word, trigger word, hotword, and wake-up word are used interchangeably.
What is Wake Word Detection?
Wake Word Detection is one of the applications of Keyword Spotting (KWS) technology. It detects (spots) phrases (keywords) in audio streams and conversations. Voice activation is the most common use case for wake word detection.
What is Trigger Word Detection?
Trigger Word Detection, Hotword Detection, and Wake Word Detection are interchangeable terms. For example, NASA uses the term hot word recognition in one project and wake word detection in another, despite using the same product: Porcupine Wake Word Detection. Google predominantly uses hotword detection but doesn’t offer custom hotwords.
How does wake word detection work?
A wake word detection engine is a binary classifier that recognizes pre-defined phrases. During training, the detection engine learns the desired wake word and how to differentiate it, so when integrated into software listens to the environment to detect that keyword.