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  1. Stackups
  2. AI
  3. Voice & Audio Models
  4. Speech Recognition Tools
  5. Haystack NLP Framework vs Speechly

Haystack NLP Framework vs Speechly

OverviewComparisonAlternatives

Overview

Speechly
Speechly
Stacks4
Followers4
Votes6
Haystack NLP Framework
Haystack NLP Framework
Stacks6
Followers12
Votes0
GitHub Stars23.2K
Forks2.5K

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Detailed Comparison

Speechly
Speechly
Haystack NLP Framework
Haystack NLP Framework

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.

Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT, etc.). It offers production-ready tools to build NLP backend services, e.g., question answering or semantic search.

Real time; Fully streaming; React client; Javascript client; iOS client; Android client; Speech recognition; Natural language understanding; Easy to configure
Question answering; Semantic document search; Latest models; Vector databases; Scalable pipelines;
Statistics
GitHub Stars
-
GitHub Stars
23.2K
GitHub Forks
-
GitHub Forks
2.5K
Stacks
4
Stacks
6
Followers
4
Followers
12
Votes
6
Votes
0
Pros & Cons
Pros
  • 2
    Easy to configure
  • 1
    Real-time visual feedback
  • 1
    Privacy options
  • 1
    Great SDKs for all platforms
  • 1
    Browser support
No community feedback yet
Integrations
React
React
React Native
React Native
ChatGPT
ChatGPT
Elasticsearch
Elasticsearch
Milvus
Milvus
FastAPI
FastAPI
OpenSearch
OpenSearch
Cohere
Cohere
Hugging Face
Hugging Face
Weaviate
Weaviate
Pinecone
Pinecone

What are some alternatives to Speechly, Haystack NLP Framework?

rasa NLU

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

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

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

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.

Clever AI Humanizer

Clever AI Humanizer

That transforms AI-generated content into natural, undetectable human-like writing. Bypass AI detection systems with intelligent text humanization technology

LangChain

LangChain

It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.

Ollama

Ollama

It allows you to run open-source large language models, such as Llama 2, locally.

Sentence Transformers

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.

LlamaIndex

LlamaIndex

It is a project that provides a central interface to connect your LLMs with external data. It offers you a comprehensive toolset trading off cost and performance.

FastText

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.

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