DeepSpeech VS nerd-dictation

Compare DeepSpeech vs nerd-dictation and see what are their differences.

DeepSpeech

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. (by mozilla)

nerd-dictation

Simple, hackable offline speech to text - using the VOSK-API. (by ideasman42)
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DeepSpeech nerd-dictation
67 28
24,086 1,141
1.3% -
0.0 3.6
about 1 month ago 15 days ago
C++ Python
Mozilla Public License 2.0 GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

DeepSpeech

Posts with mentions or reviews of DeepSpeech. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-05.
  • Common Voice
    5 projects | news.ycombinator.com | 5 Dec 2023
  • Ask HN: Speech to text models, are they usable yet?
    2 projects | news.ycombinator.com | 22 Oct 2023
  • Looking to recreate a cool AI assistant project with free tools
    3 projects | /r/selfhosted | 2 Aug 2023
    - [DeepSpeech](https://github.com/mozilla/DeepSpeech) rather than Whisper for offline speech-to-text
    3 projects | /r/techsupport | 2 Aug 2023
    I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest way to implement it using free, open-source software. Here's what he used originally, followed by some open source candidates I'm considering but would love feedback and advice before starting: Original Tools: - YoloV8 does the heavy lifting with the object detection - OpenAI Whisper handles voice - GPT-4 handles the “AI” - Google Custom Search Engine handles web browsing - MacOS/iOS handles streaming the video from my iPhone to my Mac - Python for the rest Open Source Alternatives: - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection - Replacing GPT-4 is still a challenge as I know there are some good open-source LLms like Llama 2, but I don't know how to apply this in the code perhaps in the form of api - [DeepSpeech](https://github.com/mozilla/DeepSpeech) rather than Whisper for offline speech-to-text - [Coqui TTS](https://github.com/coqui-ai/TTS) instead of Whisper for text-to-speech - Browser automation with [Selenium](https://www.selenium.dev/) instead of Google Custom Search - Stream video from phone via RTSP instead of iOS integration - Python for rest of code I'm new to working with tools like OpenCV, DeepSpeech, etc so would love any advice on the best way to replicate the original project in an open source way before I dive in. Are there any good guides or better resources out there? What are some pitfalls to avoid? Any help is much appreciated!
  • Are there any secure and free auto transcription software ?
    2 projects | /r/software | 19 Apr 2023
    If you're not afraid to get a little technical, you could take a look at mozilla/DeepSpeech (installation & usage docs here).
  • Web Speech API is (still) broken on Linux circa 2023
    8 projects | /r/javascript | 15 Apr 2023
    There is a lot of TTS and SST development going on (https://github.com/mozilla/TTS; https://github.com/mozilla/DeepSpeech; https://github.com/common-voice/common-voice). That is the only way they work: Contributions from the wild.
  • Mozilla Launches Responsible AI Challenge
    2 projects | news.ycombinator.com | 15 Mar 2023
    Mozilla did release DeepSpeech[0] and Firefox Translation[1] (the latter of which they included in Firefox, to offer client-side webpage translations.)

    They definitely have fewer resources than OpenAI, and they do not produce SOTA research (their publications have plummeted to 1/year anyway[2]). So the only way for them to make progress is to seek government grants or make challenges like these.

    This challenge is unlikely to be profitable for the winning team: the expected value of winnings are likely around $1K when taking into account the probability that another team gets a better rank, but ML research projects are often more expensive (recently, Alpaca spent upwards of $600 on computation alone; and of course pretraining large models is much more expensive). So the main gain will be publicity.

    [0]: https://github.com/mozilla/deepspeech

    [1]: https://github.com/mozilla/firefox-translations/

    [2]: https://research.mozilla.org/

  • Browserule
    2 projects | /r/196 | 25 Sep 2022
    Unfortunately, only Chrome supports the technology required to provide this feature (for now). Firefox is working to include it in the browser, but it is a complex feature that requires a lot of development. Mozilla (the company who developed Firefox) actually have a tool called DeepSpeech to use speech-to-text dictation without using the Internet. I don't know if it will help you, but I've done what I could :'(
  • speech-to-text on Linux?
    3 projects | /r/linux | 23 Aug 2022
  • Show HN: State-of-the-Art German Speech Recognition in 284 lines of C++
    5 projects | news.ycombinator.com | 10 Aug 2022
    I wrote "284 lines of C++" to indicate that this is compact enough for people to actually read and understand the source code. Also, compiling my implementation is super easy and straightforward ... something which can't be said for Kaldi, Vosk, or DeepSpeech.

    If you try to read the CTC beam search decoder from Mozilla's DeepSpeech [1], that alone is about 2000 LOC in multiple files.

    If you try to read the pyctcdecode source that is used by HuggingFace [2], that's 1000+ LOC of Python.

    But this implementation is all the client-side, i.e. the entire "native_client" folder hierarchy in DeepSpeech [3], narrowed down to a mere 284 lines.

    [1] https://github.com/mozilla/DeepSpeech/tree/master/native_cli...

    [2] https://github.com/kensho-technologies/pyctcdecode

    [3] https://github.com/mozilla/DeepSpeech/tree/master/native_cli...

nerd-dictation

Posts with mentions or reviews of nerd-dictation. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-07-07.

What are some alternatives?

When comparing DeepSpeech and nerd-dictation you can also consider the following projects:

Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.

NeMo - NeMo: a framework for generative AI

picovoice - On-device voice assistant platform powered by deep learning

STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.

TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

dicio-android - Dicio assistant app for Android

rhasspy-mobile-app - A simple mobile app for rhasspy.

Porcupine   - On-device wake word detection powered by deep learning

common-voice - Common Voice is part of Mozilla's initiative to help teach machines how real people speak.

silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple