To make a smart speaker
Here is a collection of resources to make a smart speaker.
Hope we can make an open source one for daily use.
I believe we have enough resources to make an open source smart speaker. Let's do it. Take a look at the progress of the project named
smart speaker from scratch on hackaday. The first hardware kit is available now.
The simplified flowchart of a smart speaker is like:
+---+ +----------------+ +---+ +---+ +---+ |Mic|-->|Audio Processing|-->|KWS|-->|STT|-->|NLU| +---+ +----------------+ +---+ +---+ +-+-+ | | +-------+ +---+ +----------------------+ | |Speaker|<--|TTS|<--|Knowledge/Skill/Action|<--+ +-------+ +---+ +----------------------+
- Audio Processing includes Acoustic Echo Cancellation (AEC), Beamforming, Noise Suppression (NS), etc.
- Keyword Spotting (KWS) detects a keyword (such as OK Google, Hey Siri) to start a conversation.
- Speech To Text (STT)
- Natural Language Understanding (NLU) converts raw text into structured data.
- Knowledge/Skill/Action - Knowledge base and plugins (Alexa Skill, Google Action) to provide an answer.
- Text To Speech
KWS + STT + NLU + Skill + TTS
Active open source projects
⭐- the first 100% on-device and private-by-design open-source Voice AI platform
⭐- a hackable open source voice assistant
🤖- Highly customizable, open-source, cross-platform voice assistant and VUI framework (HTML + Java + x)
- Kalliope - a framework that will help you to create your own personal assistant, kind of similar with Mycroft (Both written by Python)
- dingdang robot - a
🇨🇳voice interaction robot based on Jasper and built with raspberry pi
Amazon Alexa Voice Service - is the most widely used voice assistant
It has the smartest brain, its extension called Google Action can be created on a few steps with digitalflow.ai and its Device Action is very suit for home smart devices.
- Install Snips on Raspberry Pi 3, Linux, osX, iOS and Android
- Mycroft Precise - A lightweight, simple-to-use, RNN wake word listener
- Snowboy - DNN based hotword and wake word detection toolkit
- Honk - PyTorch reimplementation of Google's TensorFlow CNNs for keyword spotting
- ML-KWS-For-MCU - Maybe the most promise for resource constrained devices such as ARM Cortex M7 microcontroller
- Porcupine - Lightweight, cross-platform engine to build custom wake words in seconds
- Mozilla DeepSpeech - A TensorFlow implementation of Baidu's DeepSpeech architecture
- wav2letter++ - a fast, open source speech processing toolkit from the Speech team at Facebook AI Research built to facilitate research in end-to-end models for speech recognition.
- Zamia Speech - Open tools, data, models (kaldi models and wav2letter++ models) for cloudless automatic speech recognition. It can be run on Raspberry Pi
- PocketSphinx - a lightweight speech recognition engine using HMM + GMM
Snips NLU - a Python library that allows to parse sentences written in natural language and extracts structured information.
- Mozilla TTS - Deep learning for Text to Speech
- Mimic - Mycroft's TTS engine, based on CMU's Flite (Festival Lite)
- manytts - an open-source, multilingual text-to-speech synthesis system written in pure java
- espeak-ng - an open source speech synthesizer that supports 99 languages and accents.
- ekho - Chinese text-to-speech engine
- WaveNet, Tacotron 2
Acoustic Echo Cancellation
Direction Of Arrival (DOA) - Most used DOA algorithms is GCC-PHAT
- odas - ODAS stands for Open embeddeD Audition System. This is a library dedicated to perform sound source localization, tracking, separation and post-filtering. ODAS is coded entirely in C, for more portability, and is optimized to run easily on low-cost embedded hardware. ODAS is free and open source.
Voice Activity Detection
- WebRTC VAD, py-webrtcvad
- DNN VAD
- NS of WebRTC audio processing, python-webrtc-audio-processing