Innovative No-Code and Low-Code Solutions for AI-Powered Speech-to-Text Tools

Tony Kim Sep 27, 2024 07:10

Explore six no-code and low-code integrations for building AI-powered Speech-to-Text tools, enabling ease of use for those with limited coding experience.

According to AssemblyAI, AI applications are projected to contribute $15.7 trillion to the global economy by 2030, with 35% of businesses already integrating AI technology. AI-powered Speech-to-Text tools, utilizing advanced Automatic Speech Recognition (ASR) models, are becoming a cornerstone for numerous applications, including Generative AI and Audio Intelligence.

No-Code and Low-Code Integrations

1. Make

Make allows users to integrate various services to create custom tasks and workflows. The AssemblyAI app for Make enables transcription, audio data analysis, and application of LLMs to audio data.

2. Zapier

Zapier is a workflow automation tool that helps users integrate services without specialized coding knowledge. The AssemblyAI Zapier app allows users to transcribe audio and video files from various services and output the transcripts to other services.

3. Activepieces

Activepieces is an open-source, AI-first automation platform. The AssemblyAI piece for Activepieces allows for transcription, audio analysis, and application of LLMs to build Generative AI features.

4. Rivet

Rivet is an open-source visual AI programming environment. The Rivet integration supports transcription and the use of LeMUR for applying LLMs to speech data.

5. Recall

The Recall.ai and AssemblyAI integration simplifies transcription of virtual meetings, offering speaker diarization and transcription for both real-time and asynchronous streams.

6. Relay.app

Relay.app helps users streamline workflows. The AssemblyAI integration for Relay.app automates actions once transcription is complete, such as sending notifications and updating databases.

Low-Lift Coding Options

1. AssemblyAI Python SDK

Hosted on GitHub, the AssemblyAI Python SDK allows easy integration of Speech-to-Text and Audio Intelligence models. Users can transcribe audio files with minimal code.

2. AssemblyAI JavaScript SDK

The AssemblyAI JavaScript SDK supports asynchronous and real-time transcription, compatible with Node.js and other runtimes.

3. LangChain

LangChain is an open-source framework for developing applications with AI technologies. The AssemblyAI integrations for LangChain facilitate the transcription process for both Python and JavaScript frameworks.

4. Haystack

Haystack is an open-source Python framework for building NLP applications. The AssemblyAI Audio Transcript Loader allows transcription of audio files and loads the text into documents.

5. Semantic Kernel

Semantic Kernel is an SDK for developing applications with LLMs. The Semantic Kernel Integration simplifies the transcription step for speech data.

AI-Powered Speech-to-Text Use Cases

AI Speech-to-Text is being integrated across various platforms to enhance functionalities:

• Video editing platforms use AI for automatic transcription, insights, and accurate subtitles.
• Telehealth platforms leverage AI to capture conversations, summarize appointments, and analyze patient experiences.
• Ad targeting and brand protection platforms enhance contextual advertising and dynamic ad insertion.
• Sales Intelligence Platforms use AI to transcribe and analyze conversations for quick insights.
• Call analytics platforms utilize AI to speed up QA and review calls efficiently.

For further details, visit the official source.

Image source: Shutterstock

• ai
• speech-to-text
• no-code
• low-code