Simple, hackable offline speech to text - using the VOSK-API.

Overview

Nerd Dictation

Offline Speech to Text for Desktop Linux. - See demo video.

This is a utility that provides simple access speech to text for using in Linux without being tied to a desktop environment.

Simple
This is a single file Python script with minimal dependencies.
Hackable
User configuration lets you manipulate text using Python string operations.
Zero Overhead
As this relies on manual activation there are no background processes.

Dictation is accessed manually with begin/end commands.

This uses the excellent vosk-api.

Usage

It is suggested to bind begin/end/cancel to shortcut keys.

nerd-dictation begin
nerd-dictation end

For details on how this can be used, see: nerd-dictation --help and nerd-dictation begin --help.

Features

Specific features include:

Numbers as Digits

Optional conversion from numbers to digits.

So Three million five hundred and sixty second becomes 3,000,562nd.

A series of numbers (such as reciting a phone number) is also supported.

So Two four six eight becomes 2,468.

Time Out
Optionally end speech to text early when no speech is detected for a given number of seconds. (without an explicit call to end which is otherwise required).
Output Type
Output can simulate keystroke events (default) or simply print to the standard output.
User Configuration Script
User configuration is just a Python script which can be used to manipulate text using Python's full feature set.

See nerd-dictation begin --help for details on how to access these options.

Dependencies

  • Python 3.
  • The VOSK-API.
  • parec command (for recording from pulse-audio).
  • xdotool command to simulate keyboard input.

Install

pip3 install vosk
git clone https://github.com/ideasman42/nerd-dictation.git
cd nerd-dictation
wget https://alphacephei.com/kaldi/models/vosk-model-small-en-us-0.15.zip
unzip vosk-model-small-en-us-0.15.zip
mv vosk-model-small-en-us-0.15 model

To test dictation:

./nerd-dictation begin --vosk-model-dir=./model &
# Start speaking.
./nerd-dictation end
  • Reminder that it's up to you to bind begin/end/cancel to actions you can easily access (typically key shortcuts).

  • To avoid having to pass the --vosk-model-dir argument, copy the model to the default path:

    mkdir -p ~/.config/nerd-dictation
    mv ./model ~/.config/nerd-dictation

Hint

Once this is working properly you may wish to download one of the larger language models for more accurate dictation. They are available here.

Configuration

This is an example of a trivial configuration file which simply makes the input text uppercase.

# ~/.config/nerd-dictation/nerd-dictation.py
def nerd_dictation_process(text):
    return text.upper()

A more comprehensive configuration is included in the examples/ directory.

Hints

  • The processing function can be used to implement your own actions using keywords of your choice. Simply return a blank string if you have implemented your own text handling.
  • Context sensitive actions can be implemented using command line utilities to access the active window.

Paths

Local Configuration
~/.config/nerd-dictation/nerd-dictation.py
Language Model

~/.config/nerd-dictation/model

Note that --vosk-model-dir=PATH can be used to override the default.

Command Line Arguments

Output of nerd-dictation --help

usage:

nerd-dictation [-h]  ...

This is a utility that activates text to speech in Linux. While it could use any system currently it uses the VOSK-API.

positional arguments:

begin: Begin dictation.
end: End dictation.
cancel: Cancel dictation.
optional arguments:
-h, --help show this help message and exit

Subcommand: begin

usage:

nerd-dictation begin [-h] [--cookie FILE_PATH] [--vosk-model-dir DIR]
                     [--pulse-device-name IDENTIFIER]
                     [--sample-rate HZ] [--defer-output] [--continuous]
                     [--timeout SECONDS] [--idle-time SECONDS]
                     [--delay-exit SECONDS]
                     [--punctuate-from-previous-timeout SECONDS]
                     [--full-sentence] [--numbers-as-digits]
                     [--numbers-use-separator] [--output OUTPUT_METHOD]
                     [- ...]

This creates the directory used to store internal data, so other commands such as sync can be performed.

optional arguments:
-h, --help show this help message and exit
--cookie FILE_PATH
  Location for writing a temporary cookie (this file is monitored to begin/end dictation).
--vosk-model-dir DIR
  Path to the VOSK model, see: https://alphacephei.com/vosk/models
--pulse-device-name IDENTIFIER
  The name of the pulse-audio device to use for recording. See the output of "pactl list sources" to find device names (using the identifier following "Name:").
--sample-rate HZ
  The sample rate to use for recording (in Hz). Defaults to 44100.
--defer-output

When enabled, output is deferred until exiting.

This prevents text being typed during speech (implied with --output=STDOUT)

--continuous Enable this option, when you intend to keep the dictation process enabled for extended periods of time. without this enabled, the entirety of this dictation session will be processed on every update. Only used when --defer-output is disabled.
--timeout SECONDS
  Time out recording when no speech is processed for the time in seconds. This can be used to avoid having to explicitly exit (zero disables).
--idle-time SECONDS
  Time to idle between processing audio from the recording. Setting to zero is the most responsive at the cost of high CPU usage. The default value is 0.1 (processing 10 times a second), which is quite responsive in practice (the maximum value is clamped to 0.5)
--delay-exit SECONDS
  The time to continue running after an exit request. this can be useful so "push to talk" setups can be released while you finish speaking (zero disables).
--punctuate-from-previous-timeout SECONDS
  The time-out in seconds for detecting the state of dictation from the previous recording, this can be useful so punctuation it is added before entering the dictation(zero disables).
--full-sentence
  Capitalize the first character. This is also used to add either a comma or a full stop when dictation is performed under the --punctuate-from-previous-timeout value.
--numbers-as-digits
  Convert numbers into digits instead of using whole words.
--numbers-use-separator
  Use a comma separators for numbers.
--output OUTPUT_METHOD
 

Method used to at put the result of speech to text.

  • SIMULATE_INPUT simulate keystrokes (default).
  • STDOUT print the result to the standard output. Be sure only to handle text from the standard output as the standard error may be used for reporting any problems that occur.
- ... End argument parsing.
This can be used for user defined arguments which configuration scripts may read from the sys.argv.

Subcommand: end

usage:

nerd-dictation end [-h] [--cookie FILE_PATH]

This ends dictation, causing the text to be typed in.

optional arguments:
-h, --help show this help message and exit
--cookie FILE_PATH
  Location for writing a temporary cookie (this file is monitored to begin/end dictation).

Subcommand: cancel

usage:

nerd-dictation cancel [-h] [--cookie FILE_PATH]

This cancels dictation.

optional arguments:
-h, --help show this help message and exit
--cookie FILE_PATH
  Location for writing a temporary cookie (this file is monitored to begin/end dictation).

Details

  • Typing in results will never press enter/return.
  • Pulse audio is used for recording.
  • Recording and speech to text a performed in parallel.

Examples

Store the result of speech to text as a variable in the shell:

SPEECH="$(nerd-dictation begin --timeout=1.0 --output=STDOUT)"

Example Configurations

These are example configurations you may use as a reference.

Other Software

  • Elograf - nerd-dictation GUI front-end that runs as a tray icon.

Limitations

  • Text from VOSK is all lower-case, while the user configuration can be used to set the case of common words like I this isn't very convenient (see the example configuration for details).

  • For some users the delay in start up may be noticeable on systems with slower hard disks especially when running for the 1st time (a cold start).

    This is a limitation with the choice not to use a service that runs in the background. Recording begins before any the speech-to-text components are loaded to mitigate this problem.

Further Work

  • And a general solution to capitalize words (proper nouns for example).
  • Wayland support (this should be quite simple to support and mainly relies on a replacement for xdotool).
  • Add a setup.py for easy installation on uses systems.
  • Possibly other speech to text engines (only if they provide some significant benefits).
  • Possibly support Windows & macOS.
Owner
Campbell Barton
Campbell Barton
Must-read papers on improving efficiency for pre-trained language models.

Must-read papers on improving efficiency for pre-trained language models.

Tobias Lee 89 Jan 03, 2023
Negative sampling for solving the unlabeled entity problem in NER. ICLR-2021 paper: Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition.

Negative Sampling for NER Unlabeled entity problem is prevalent in many NER scenarios (e.g., weakly supervised NER). Our paper in ICLR-2021 proposes u

Yangming Li 128 Dec 29, 2022
nlpcommon is a python Open Source Toolkit for text classification.

nlpcommon nlpcommon, Python Text Tool. Guide Feature Install Usage Dataset Contact Cite Reference Feature nlpcommon is a python Open Source

xuming 3 May 29, 2022
NLP library designed for reproducible experimentation management

Welcome to the Transfer NLP library, a framework built on top of PyTorch to promote reproducible experimentation and Transfer Learning in NLP You can

Feedly 290 Dec 20, 2022
Based on 125GB of data leaked from Twitch, you can see their monthly revenues from 2019-2021

Twitch Revenues Bu script'i kullanarak istediğiniz yayıncıların, Twitch'den sızdırılan 125 GB'lik veriye dayanarak, 2019-2021 arası aylık gelirlerini

4 Nov 11, 2021
This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini!

About CappuccinoJs This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini! Este conversor criar

Arthur Ottoni Ribeiro 48 Nov 15, 2022
Implementation of paper Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa.

RoBERTaABSA This repo contains the code for NAACL 2021 paper titled Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoB

106 Nov 28, 2022
Python bindings to the dutch NLP tool Frog (pos tagger, lemmatiser, NER tagger, morphological analysis, shallow parser, dependency parser)

Frog for Python This is a Python binding to the Natural Language Processing suite Frog. Frog is intended for Dutch and performs part-of-speech tagging

Maarten van Gompel 46 Dec 14, 2022
Framework for fine-tuning pretrained transformers for Named-Entity Recognition (NER) tasks

NERDA Not only is NERDA a mesmerizing muppet-like character. NERDA is also a python package, that offers a slick easy-to-use interface for fine-tuning

Ekstra Bladet 141 Dec 30, 2022
BiQE: Code and dataset for the BiQE paper

BiQE: Bidirectional Query Embedding This repository includes code for BiQE and the datasets introduced in Answering Complex Queries in Knowledge Graph

Bhushan Kotnis 1 Oct 20, 2021
Translate U is capable of translating the text present in an image from one language to the other.

Translate U is capable of translating the text present in an image from one language to the other. The app uses OCR and Google translate to identify and translate across 80+ languages.

Neelanjan Manna 1 Dec 22, 2021
Idea is to build a model which will take keywords as inputs and generate sentences as outputs.

keytotext Idea is to build a model which will take keywords as inputs and generate sentences as outputs. Potential use case can include: Marketing Sea

Gagan Bhatia 364 Jan 03, 2023
Blue Brain text mining toolbox for semantic search and structured information extraction

Blue Brain Search Source Code DOI Data & Models DOI Documentation Latest Release Python Versions License Build Status Static Typing Code Style Securit

The Blue Brain Project 29 Dec 01, 2022
What are the best Systems? New Perspectives on NLP Benchmarking

What are the best Systems? New Perspectives on NLP Benchmarking In Machine Learning, a benchmark refers to an ensemble of datasets associated with one

Pierre Colombo 12 Nov 03, 2022
Help you discover excellent English projects and get rid of disturbing by other spoken language

GitHub English Top Charts 「Help you discover excellent English projects and get

GrowingGit 544 Jan 09, 2023
Ray-based parallel data preprocessing for NLP and ML.

Wrangl Ray-based parallel data preprocessing for NLP and ML. pip install wrangl # for latest pip install git+https://github.com/vzhong/wrangl See exa

Victor Zhong 33 Dec 27, 2022
Bnagla hand written document digiiztion

Bnagla hand written document digiiztion This repo addresses the problem of digiizing hand written documents in Bangla. Documents have definite fields

Mushfiqur Rahman 1 Dec 10, 2021
pyupbit 라이브러리를 활용하여 upbit에서 비트코인을 자동매매하는 코드입니다. 조코딩 유튜브 채널에서 자세한 강의 영상을 보실 수 있습니다.

파이썬 비트코인 투자 자동화 강의 코드 by 유튜브 조코딩 채널 pyupbit 라이브러리를 활용하여 upbit 거래소에서 비트코인 자동매매를 하는 코드입니다. 파일 구성 test.py : 잔고 조회 (1강) backtest.py : 백테스팅 코드 (2강) bestK.p

조코딩 JoCoding 186 Dec 29, 2022
Input english text, then translate it between languages n times using the Deep Translator Python Library.

mass-translator About Input english text, then translate it between languages n times using the Deep Translator Python Library. How to Use Install dep

2 Mar 04, 2022
Question answering app is used to answer for a user given question from user given text.

Question answering app is used to answer for a user given question from user given text.It is created using HuggingFace's transformer pipeline and streamlit python packages.

Siva Prakash 3 Apr 05, 2022