By DaVoice.io
Welcome to Davoice WakeWord / Keywords Detection – Wake words and keyword detection solution designed by DaVoice.io.
This is a "wake word" package for Python.
A "wake word" is a keyword or a phrase that activates your device or commands your application, like "Hey Siri" or "OK Google". "Wake Word" is also known as "keyword detection", "Phrase Recognition", "Phrase Spotting", “Voice triggered”, “hotword”, “trigger word”
Except for "Python wake word" It also provide "Python Speech to Intent". Speech to Intent refers to the ability to recognize a spoken word or phrase and directly associate it with a specific action or operation within an application. Unlike a "wake word", which typically serves to activate or wake up the application, Speech to Intent goes further by enabling complex interactions and functionalities based on the recognized intent behind the speech.
For example, a wake word like "Hey App" might activate the application, while Speech to Intent could process a phrase like "Play my favorite song" or "Order a coffee" to execute corresponding tasks within the app. Speech to Intent is often triggered after a wake word activates the app, making it a key component of more advanced voice-controlled applications. This layered approach allows for seamless and intuitive voice-driven user experiences.
- Easy to use and deploy with Python: Check out our example code and install scripts.
- Cross-Platform Support: Integrate Davoice "Python wake word" into most known HW architectures and OS.
- Low Latency: Experience near-instantaneous keyword detection.
- High Accuracy: We have successfully reached over 99% accuracy for all our models.
- Real-World Benchmarks: At DaVoice, we believe in real benchmarks done by customers on actual use cases rather than static tests. We actively encourage our customers to share their real-world experiences and results.
Provided by Tyler Troy, CTO & Co-Founder of LookDeep Health
Tyler Troy conducted an independent benchmark at LookDeep Health to select a "phrase detection" vendor.
- This is THE most crucial criteria, in hospital settings, false alerts are unacceptable—they waste valuable time and can compromise patient care.
- ✅ DaVoice: "ZERO FALSE POSITIVES" within a month duration of testing.
- In contrast, Picovoice triggered several false alerts during testing, making it unsuitable for critical environments like hospitals.
- OpenWakeWord was not tested for false positives because its true positive rate was too low.
Table 1: A comparison of model performance on custom keywords
MODEL DETECTION RATE
===========================
DaVoice 0.992481
Porcupine (Picovoice) 0.924812
OpenWakeWords 0.686567
Read Tyler Troy, CTO & Co-Founder of LookDeep, Reddit post:
Bulletproof Wakeword/Keyword Spotting
Benchmark on "Python wake word", vs top competitors:
- Benmark used recordings with 1326 TP files.
- Second best was on of the industry top players who detected 1160 TP
- Third detected TP 831 out of 1326
MODEL DETECTION RATE
===========================
DaVoice 0.992458
Top Player 0.874811
Third 0.626697
- "Python wake word " on linux.x86_64
- "Python wake word " on linux.aarch64
- "Python wake word " on linux.armv7
- "Python wake word " on linux.ppc64
- "Python wake word " on linux.ppc64le
- "Python wake word " on linux.s390x
- "Python wake word " on darwin.x86_64
- "Python wake word" on darwin.arm64
- "Python wake word" on win32
- "Python wake word" on win_amd64
- "Python wake word" on win.arm64
In order to generate your "custom wake word" you will need to:
-
Create Python wake word model: Contact us at [email protected] with a list of your desired "custom wake words".
We will send you corresponding models typically your wake word phrase .onnx for example:
A wake word *"hey sky" will correspond to hey_sky.onnx.
-
Add wake words to Python example: Simply copy your model onnx files to: example/models/
In example.py change the "need_help_now.onnx" to your model.onnx keyword_detection_models = ["models/need_help_now.onnx"] run python example.py
For any questions, requirements, or more support for other platforms, please contact us at [email protected].
Clone this repo
Please edit the installation files (install.sh or first_time_install.sh) and change PYTHON_VERSION=3.12 to your python version!!!
source first_time_installation.sh
source install.sh
Please edit the installation files and change PYTHON_VERSION=3.12 to your python version!!!
$ cd example $ python example.py
See example
- "Python Wake Word" API Reference
- frymanofer.github.io
Our customers have benchmarked our technology against leading solutions, including Picovoice Porcupine, Snowboy, Pocketsphinx, Sensory, and others. In several tests, our performance was comparable to Picovoice Porcupine, occasionally surpassing it, however both technologies consistently outperformed all others in specific benchmarks. For detailed references or specific benchmark results, please contact us at [email protected].
DaVoice.io Voice commands / Wake words / Voice to Intent / keyword detection npm for Android and IOS. "Python Wake word detection github" "Python Wake word detection", "Python Wake word", "Python Phrase Recognition", "Python Phrase Spotting", “Python Voice triggered”, “Python hotword”, “Python trigger word”, "Wake word detection Python" "react-native wake word", "Wake word detection github", "Wake word generator", "Custom wake word", "voice commands", "wake word", "wakeword", "wake words", "keyword detection", "keyword spotting", "speech to intent", "voice to intent", "phrase spotting", "react native wake word", "Davoice.io wake word", "Davoice wake word", "Davoice react native wake word", "Davoice react-native wake word", "wake", "word", "Voice Commands Recognition", "lightweight Voice Commands Recognition", "customized lightweight Voice Commands Recognition", "rn wake word"
Here are wakeword detection GitHub links per platform:
- Web / JS / Angular / React: https://github.com/frymanofer/Web_WakeWordDetection/tree/main
- For React Native: ReactNative_WakeWordDetection
- For Android: KeywordsDetectionAndroidLibrary
- For iOS framework:
- With React Native bridge: KeyWordDetectionIOSFramework
- Sole Framework: KeyWordDetection