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/local |
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FROM debian:bookworm-slim | ||
ARG TARGETARCH | ||
ARG TARGETVARIANT | ||
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# Install wyoming-vosk | ||
WORKDIR /usr/src | ||
ENV WYOMING_VOSK_VERSION=1.0.0 | ||
ENV PIP_BREAK_SYSTEM_PACKAGES=1 | ||
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RUN \ | ||
apt-get update \ | ||
&& apt-get install -y --no-install-recommends \ | ||
python3 \ | ||
python3-pip \ | ||
&& pip3 install --no-cache-dir -U \ | ||
setuptools \ | ||
wheel \ | ||
&& pip3 install --no-cache-dir \ | ||
--extra-index-url https://www.piwheels.org/simple \ | ||
-f . \ | ||
"wyoming-vosk[limited] @ https://github.com/rhasspy/wyoming-vosk/archive/refs/tags/v${WYOMING_VOSK_VERSION}.tar.gz" \ | ||
&& rm -rf /var/lib/apt/lists/* | ||
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WORKDIR / | ||
COPY run.sh ./ | ||
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EXPOSE 10300 | ||
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ENTRYPOINT ["bash", "/run.sh"] |
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.PHONY: local run update | ||
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VERSION := 1.0.0 | ||
TAG := rhasspy/wyoming-vosk | ||
PLATFORMS := linux/amd64,linux/arm64,linux/arm/v7 | ||
HOST := 0.0.0.0 | ||
PORT := 10300 | ||
DATA_DIR := $(PWD)/local | ||
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all: | ||
docker buildx build . --platform "$(PLATFORMS)" --tag "$(TAG):$(VERSION)" --push | ||
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update: | ||
docker buildx build . --platform "$(PLATFORMS)" --tag "$(TAG):latest" --push | ||
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local: | ||
docker build . -t "$(TAG):$(VERSION)" --build-arg TARGETARCH=amd64 | ||
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run: | ||
docker run -it -p "$(PORT):$(PORT)" -v "$(DATA_DIR):$(DATA_DIR)" "$(TAG):$(VERSION)" --uri 'tcp://$(HOST):$(PORT)' --data-dir "$(DATA_DIR)" --debug |
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# vosk | ||
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[Wyoming protocol](https://github.com/rhasspy/wyoming) server for the [vosk](https://alphacephei.com/vosk) speech to text system, with optional sentence correction using [rapidfuzz](https://github.com/maxbachmann/RapidFuzz). | ||
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This speech-to-text system can run well, even on a Raspberry Pi 3. Using the corrected or limited modes (described below), you can achieve very high accuracy by restricting the sentences that can be spoken. | ||
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## Modes | ||
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There are three operating modes: | ||
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1. Open-ended - any sentence can be spoken, but recognition is very poor compared to [Whisper](https://github.com/rhasspy/wyoming-faster-whisper) | ||
2. Corrected - sentences similar to [templates](#sentence-templates) are forced to match | ||
3. Limited - only sentences from [templates](#sentence-templates) can be spoken | ||
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### Open-ended | ||
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This is the default mode: transcripts from [vosk](https://alphacephei.com/vosk) are used directly. | ||
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Recognition is very poor compared to [Whisper](https://github.com/rhasspy/wyoming-faster-whisper) unless you use one of the [larger models](https://alphacephei.com/vosk/models). | ||
To use a specific model, such as `vosk-model-en-us-0.21` (1.6GB): | ||
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1. Download and extract the model to a directory (`<DATA_DIR>`) so that you have `<DATA_DIR>/vosk-model-en-us-0.21` | ||
2. Run `wyoming_vosk` with `--data-dir <DATA_DIR>` and `--model-for-language en vosk-model-en-us-0.21` | ||
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Note that `wyoming_vosk` will only automatically download models listed in `download.py`. | ||
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### Corrected | ||
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By specifying which sentences will be spoken ahead of time, transcripts from vosk can be corrected using [rapidfuzz](https://github.com/maxbachmann/RapidFuzz). | ||
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Create your [sentence templates](#sentence-templates) and save them to a file named `<SENTENCES_DIR>/<LANGUAGE>.yaml` where `<LANGUAGE>` is one of the [supported language codes](#supported-languages). For example, English sentences should be saved in `<SENTENCES_DIR>/en.yaml`. | ||
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Then, run `wyoming_vosk` like: | ||
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``` sh | ||
script/run ... --sentences-dir <SENTENCES_DIR> --correct-sentences <CUTOFF> | ||
``` | ||
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where `<CUTOFF>` is: | ||
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* empty or 0 - force transcript to be one of the template sentences | ||
* 1-100 - allow more sentences that are not similar to templates to pass through | ||
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When `<CUTOFF>` is 100, speech recognition is effectively open-ended again. Experiment with different values to find one that lets you speak sentences outside your templates without sacrificing accuracy too much. | ||
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If you have a set of sentences with a specific pattern that you'd like to skip correction, add them to your [no-correct patterns](#no-correct-patterns). | ||
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### Limited | ||
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Follow the instructions for [corrected mode](#corrected), then run `wyoming_vosk` like: | ||
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``` sh | ||
script/run ... --sentences-dir <SENTENCES_DIR> --correct-sentences --limit-sentences | ||
``` | ||
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This will tell vosk that **only** the sentences from you templates can ever be spoken. Sentence correction is still needed (due to how vosk works internally), but it will ensure that sentences outside the templates cannot be sent. | ||
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This mode will get you the highest possible accuracy, with the trade-off being that you cannot speak sentences outside the templates. | ||
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## Sentence Templates | ||
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Each language may have a YAML file with [sentence templates](https://github.com/home-assistant/hassil#sentence-templates). | ||
Most syntax is supported, including: | ||
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* Optional words, surrounded with `[square brackets]` | ||
* Alternative words, `(surrounded|with|parens)` | ||
* Lists of values, referenced by `{name}` | ||
* Expansion rules, inserted by `<name>` | ||
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The general format of a language's YAML file is: | ||
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``` yaml | ||
sentences: | ||
- this is a plain sentence | ||
- this is a sentence with a {list} and a <rule> | ||
lists: | ||
list: | ||
values: | ||
- value 1 | ||
- value 2 | ||
expansion_rules: | ||
rule: body of the rule | ||
``` | ||
Sentences have a special `in/out` form as well, which lets you say one thing (`in`) but put something else in the transcript (`out`). | ||
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For example: | ||
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``` yaml | ||
sentences: | ||
- in: lumos | ||
out: turn on all the lights | ||
- in: nox | ||
out: turn off all the lights | ||
``` | ||
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lets you say "lumos" to send "turn on all the lights", and "nox" to send "turn off all the lights". | ||
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The `in` key can also take a list of sentences, all of them outputting the same `out` string. | ||
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### Lists | ||
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Lists are useful when you many possible words/phrases in a sentence. | ||
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For example: | ||
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``` yaml | ||
sentences: | ||
- set light to {color} | ||
lists: | ||
color: | ||
values: | ||
- red | ||
- green | ||
- blue | ||
- orange | ||
- yellow | ||
- purple | ||
``` | ||
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lets you set a light to one of six colors. | ||
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This could also be written as `set light to (red|green|blue|orange|yellow|purple)`, but the list is more manageable and can be shared between sentences. | ||
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List values have a special `in/out` form that lets you say one thing (`in`) but put something else in the transcript (`out`). | ||
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For example: | ||
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``` yaml | ||
sentences: | ||
- turn (on|off) {device} | ||
lists: | ||
device: | ||
values: | ||
- in: tv | ||
out: living room tv | ||
- in: light | ||
out: bedroom room light | ||
``` | ||
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lets you say "turn on tv" to turn on the living room TV, and "turn off light" to turn off the bedroom light. | ||
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### Expansion Rules | ||
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Repeated parts of a sentence template can be abstracted into an expansion rule. | ||
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For example: | ||
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``` yaml | ||
sentences: | ||
- turn on <the> light | ||
- turn off <the> light | ||
expansion_rules: | ||
the: [the|my] | ||
``` | ||
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lets you say "turn on light" or "turn off my light" without having to repeat the optional part. | ||
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## No Correct Patterns | ||
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When you [correct sentences](#correct-sentences), you want to keep the score cutoff as low as possible to avoid letting invalid sentences though. But what if you just want *some* open-ended sentences, such as "draw me a picture of ..." which you can then forward to an image generator? | ||
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Add the following to your sentences YAML file: | ||
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``` yaml | ||
sentences: | ||
... | ||
no_correct_patterns: | ||
- <regular expression> | ||
- <regular expression> | ||
... | ||
``` | ||
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You can add as many regular expressions to `no_correct_patterns` as you'd like. If the transcript matches any of these patterns, it will be sent with no further corrections. This effectively lets you "punch holes" in the sentence templates to allow some sentences through. | ||
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## Allow Unknown | ||
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With `--allow-unknown`, you can enable the detection of "unknown" words/phrases outside of the model's vocabulary. Transcripts that are "unknown" will be set to empty strings, indicating that nothing was recognized. When combined with [limited sentences](#limited-sentences), this lets you differentiate between in and out of domain sentences. | ||
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## Supported Languages | ||
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* Arabic (`ar`) | ||
* Breton (`br`) | ||
* Catalan (`ca`) | ||
* Czech (`cz`) | ||
* German (`de`) | ||
* English (`en`) | ||
* Esperanto (`eo`) | ||
* Spanish (`es`) | ||
* Persian (`fa`) | ||
* French (`fr`) | ||
* Hindi (`hi`) | ||
* Italian (`it`) | ||
* Japanese (`ja`) | ||
* Korean (`ko`) | ||
* Kazakh (`kz`) | ||
* Dutch (`nl`) | ||
* Polish (`pl`) | ||
* Portuguese (`pt`) | ||
* Russian (`ru`) | ||
* Swedish (`sv`) | ||
* Tagalog (`tl`) | ||
* Ukrainian (`uk`) | ||
* Uzbek (`uz`) | ||
* Vietnamese (`vn`) | ||
* Chinese (`zh`) |
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#!/usr/bin/env bash | ||
python3 -m wyoming_vosk \ | ||
--uri 'tcp://0.0.0.0:10300' "$@" |