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What is SpeechText.AI?

Effortlessly transform audio and video files into precise written text. Obtain top-notch transcriptions for your podcasts with specialized speech recognition optimized for various industries. SpeechText.AI is a sophisticated software solution that effectively converts spoken words into text format. Users can conveniently upload their audio or video files, reaping the benefits of AI-driven transcription that supports multiple formats and languages. By selecting the relevant domain and audio type from established categories, users can improve the accuracy of transcribing industry-specific jargon. Once the appropriate settings are chosen, the advanced transcription engine utilizes state-of-the-art deep neural network models to generate text that mirrors human accuracy. Furthermore, users are empowered to interactively edit, search, and verify their transcriptions through intuitive editing tools, with the option to export the completed content in various formats. The impressive suite of features within SpeechText.AI ensures that audio and video transcription is achieved in just seconds, made possible by its robust speech recognition technology. With its accessible interface and leading-edge capabilities, SpeechText.AI is well-equipped to fulfill all your transcription requirements, making it an invaluable resource for professionals across diverse fields.

What is CATalyst Check It?

Check It serves as a highly beneficial feature for Stenograph's CATalyst software, designed to enhance the editing workflow for both court reporters and scopists alike. By leveraging Phoenix, Stenograph's exclusive Automatic Speech Recognition (ASR) engine tailored for the legal field, Check It thoroughly examines the audio from court sessions in tandem with the related transcript, identifying discrepancies and providing recommendations for corrections. This innovative tool greatly boosts editing productivity by reducing the number of keystrokes required and simplifying text adjustments, enabling users to potentially recover up to 3.75 hours of editing time weekly. The time reclaimed allows reporters the opportunity to accept up to two additional assignments, which could lead to a significant increase in earnings of at least $1000 per month, while scopists might enjoy an extra $800 in their monthly income. By fusing the advanced capabilities of Phoenix with the skills of reporters, Check It becomes an essential resource for enhancing transcripts, thus facilitating an efficient editing process and optimizing overall productivity. Additionally, the collaboration between advanced technology and professional expertise not only elevates the quality of individual work but also enhances the precision and reliability of legal documents across the board.

Media

Media

Integrations Supported

Quickwork
Stenograph Phoenix

Integrations Supported

Quickwork
Stenograph Phoenix

API Availability

Has API

API Availability

Has API

Pricing Information

$19 one-time payment
Free Trial Offered?
Free Version

Pricing Information

$49 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

SpeechText.AI

Date Founded

2019

Company Location

Germany

Company Website

speechtext.ai

Company Facts

Organization Name

Stenograph

Date Founded

1938

Company Location

United States

Company Website

www.stenograph.com/checkit

Categories and Features

Speech Recognition

Audio Capture
Automatic Form Fill
Automatic Transcription
Call Analysis
Concatenated Speech
Continuous Speech
Customizable Macros
Multi-Languages
Specialty Vocabularies
Speech-to-Text Analysis
Variable Frequency
Voice Recognition

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