Whisper vs Speechly
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions. | It is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. |
Real time; Fully streaming; React client; Javascript client; iOS client; Android client; Speech recognition; Natural language understanding; Easy to configure | Automatic speech recognition;
Trained on a large dataset of diverse audio;
Multi-task model;
Can perform multilingual speech recognition;
Can perform speech translation and language identification |
Statistics | |
GitHub Stars - | GitHub Stars 90.3K |
GitHub Forks - | GitHub Forks 11.3K |
Stacks 4 | Stacks 24 |
Followers 4 | Followers 28 |
Votes 6 | Votes 1 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
What are some alternatives to Speechly, Whisper?
rasa NLU
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
SpaCy
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
MonkeyLearn
Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.
Jina
It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
Grok-1
It is the base model weights and network architecture of Grok-1, the large language model. Grok-1 is a 314 billion parameter Mixture-of-Experts model trained from scratch by xAI.
Google Gemini
It is Google’s largest and most capable AI model. It is built to be multimodal, it can generalize, understand, operate across, and combine different types of info — like text, images, audio, video, and code.
LLaMA
It is a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI.
Sentence Transformers
It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.
FastText
It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.
CoreNLP
It provides a set of natural language analysis tools written in Java. It can take raw human language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize and interpret dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases or word dependencies, and indicate which noun phrases refer to the same entities.
