Kaldi
CMU Sphinx
Microsoft Bing Speech API
Express Scribe
HTK
Microsoft Speaker Recognition API
Craft Coffee
Think-A-Move SPEAR Speech Recognition
Speechly
AssemblyAI
Voice Elements
Deepgram
SpeechFlow.io
Google Cloud Speech API
Wiz Write
Speechmatics
Speechly is a developer tool that enables adding intuitive voice functionalities to any application.
Our fully streaming API returns transcript, user intent and entities in real-time, instead of only after the utterance as is the case of voice assistants and smart speakers. This encourages users to use more complex voice input and enables them to correct themselves naturally in case of errors.
Kaldi SpeechlyNo features have been listed yet.
Based on our record, Kaldi seems to be more popular. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Yeah, whisper is the closest thing we have, but even it requires more processing power than is present in most of these edge devices in order to feel smooth. I've started a voice interface project on a Raspberry Pi 4, and it takes about 3 seconds to produce a result. That's impressive, but not fast enough for Alexa. From what I gather a Pi 5 can do it in 1.5 seconds, which is closer, so I suspect it's only a... - Source: Hacker News / 5 months ago
You can study CTC in isolation, ignoring all the HMM background. That is how CTC was also originally introduced, by mostly ignoring any of the existing HMM literature. So e.g. Look at the original CTC paper. But I think the distill.pub article (https://distill.pub/2017/ctc/) is also good. For studying HMMs, any speech recognition lecture should cover that. We teach that at RWTH Aachen University but I don't think... - Source: Hacker News / 8 months ago
I also tried Kaldi but the build process was too much for my tiny brain; I've also heard good things about vosk but didn't try that. Source: about 1 year ago
Frameworks as well as toolkits like Kaldi were at first promoted by the research study area, yet nowadays used by both scientists and also market experts, reduced the access obstacle in the advancement of automatic speech recognition systems. Nonetheless, cutting edge methods need big speech data readies to achieve a usable system. Source: over 1 year ago
If you interested in unix-like software design and not yet familiar with kaldi toolkit, you definitely need to check it https://kaldi-asr.org It extended Unix design with archives, control lists and matrices and enabled really flexible unix-like processing. For example, recognition of a dataset looks like this: extract-wav scp:list.scp ark:- | compute-mfcc-feats ark:- ark:- | lattice-decoder-faster final.mdl... - Source: Hacker News / over 1 year ago
CMU Sphinx - CMU Sphinx is a speaker-independent large vocabulary continuous speech recognizer released under...
AssemblyAI - Speech Recognition for Everyone and Everything.
Microsoft Bing Speech API - Compare pricing options for the Bing Speech API through Microsoft Azure Cognitive Services. Learn how to buy various pricing options that work best for your business.
Voice Elements - Web components that do amazing things w/ the web speech api
Express Scribe - Express Scribe transcription software and audio player specifically designed for typists.
Deepgram - Search engine for speech
