coral-pi-rest-server
larynx
coral-pi-rest-server | larynx | |
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44 | 18 | |
66 | 788 | |
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0.0 | 0.0 | |
7 months ago | 11 months ago | |
Jupyter Notebook | Python | |
MIT License | MIT License |
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coral-pi-rest-server
- BeagleY-AI: 4 TOPS-capable $70 board from Beagleboard
- Do you recommend Orange PI for ML or LLM projects?
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Framework for machine learning?
That said, you can always look at something like https://coral.ai/products/accelerator/ to help with the performance you need.
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Mini PC for AI
Should only be ~$60 https://coral.ai/products/accelerator/
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What are some USB devices worth using in a Home Lab Environment?
The Coral USB accelerator might be of interest if you want to do some light ML with a low power budget.
- Is a PCIe x1 enough for light ML tasks
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Would I be able to run ggml models such as whisper.cpp or llama.cpp on a raspberry pi with a coral ai USB Accelerator?
However, a pi doesn't have the strength to run something like Llama.cpp, of course, so I've been considering using something like the Coral USB Accelerator (https://coral.ai/products/accelerator). As I've been learning more about it, it seems to be very geared towards TensorFlow Lite models. But whisper.cpp and Llama.cpp use ggml models.
- Looking for a Mini PC for Home Assistant and Frigate.
- AI development suite on a stick?
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Modder wires ChatGPT into Skyrim VR so NPCs can roleplay and remember past conversations
Recently found this thing, though I haven't found a use case for me.
larynx
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Home Assistant’s Year of the Voice – Chapter 2
The most exciting thing about Home Assistant's "Year of the Voice", for me, is that it is apparently enabling/supporting @synesthesiam's continued phenomenal contributions to the FLOSS off-line voice synthesis space.
The quality, variety & diversity of voices that synesthesiam's "Larynx" TTS project (https://github.com/rhasspy/larynx/) made available, completely transformed the Free/Open Source Text To Speech landscape.
In addition "OpenTTS" (https://github.com/synesthesiam/opentts) provided a common API for interacting with multiple FLOSS TTS projects which showed great promise for actually enabling "standing on the shoulders of" rather than re-inventing the same basic functionality every time.
The new "Piper" TTS project mentioned in the article is the apparent successor to Larynx and, along with the accompanying LibriTTS/LibriVox-based voice models, brings to FLOSS TTS something it's never had before:
* Too many voices! :)
Seriously, the current LibriTTS voice model version has 900+ voices (of varying quality levels), how do you even navigate that many?![0]
And that's not even considering the even higher quality single speaker models based on other audio recording sources.
Offline TTS while immensely valuable for individuals, doesn't seem to be attractive domain for most commercial entities due to lack of lock-in/telemetry opportunities so I was concerned that we might end up missing out on further valuable contributions from synesthesiam's specialised skills & experience due to financial realities & the human need for food. :)
I'm glad we instead get to see what happens next.
[0] See my follow-up comment about this.
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Text to speech
Larynx!
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Ask HN: Are there any good open source Text-to-Speech tools?
I've had good results with https://github.com/rhasspy/larynx
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Recommend a Text to Speech tool ?
Larynx is a really good text-to-speech engine
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Klipper on android
I was able to install 3.7 following this guide. https://github.com/rhasspy/larynx/issues/9
- I built an audio only Gemini client.
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NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
If you've not already encountered them I'd definitely encourage you to check out these Free/Open Source projects too:
* Larynx: https://github.com/rhasspy/larynx/
* OpenTTS: https://github.com/synesthesiam/opentts
* Likely Mimic3 in the near future: https://mycroft.ai/blog/mimic-3-preview/
Larynx in particular has a focus on "faster than real-time" while OpenTTS is an attempt to package & provide common REST API to all Free/Open Source Text To Speech systems so the FLOSS ecosystem can build on previous work supported by short-lived business interests, rather than start from scratch every time.
AIUI the developer of the first two projects now works for Mycroft AI & is involved in the development of Mimic3 which seems very promising given how much of an impact on quality his solo work has had in just the past couple of years or so.
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Need a recommendation: Self hosted speech to text service
I haven't used it on it's own, but Larynx has worked well for me for Rhasspy
- NATSpeech: High Quality Text-to-Speech Implementation with HuggingFace Demo
- Question: Does anybody know of a working Text to Speech for python on pi?
What are some alternatives?
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
double-take - Unified UI and API for processing and training images for facial recognition.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
rpi-urban-mobility-tracker - The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.
RHVoice - a free and open source speech synthesizer for Russian and other languages
opentts - Open Text to Speech Server
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
HASS-coral-rest-api - Coral REST API for HASS
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
os-nvr
rhasspy - Offline private voice assistant for many human languages