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Average Ratings 0 Ratings
Description
Paraspeech is an innovative speech-to-text application designed for Mac and iOS that effortlessly converts spoken ideas into organized text using an intuitive process of holding a button, speaking, and then releasing. For Mac users, the procedure involves pressing and holding a designated hotkey within the app at the desired writing location, speaking in a natural tone, and then releasing the key; Paraspeech then processes the captured audio and strives to insert the text directly into the currently active field, utilizing clipboard support for areas that do not accept direct input. Users with Apple Silicon Macs benefit from supported local speech modes, enabling transcription directly on the device and offline functionality after initial configuration, while various cloud-based options remain accessible based on the chosen backend. The application features swift local models that cater to multiple languages, including English, Japanese, Mandarin Chinese, and offers dictation support for 25 languages, while the Multilingual Large model expands its reach to over 100 languages where feasible. Moreover, the AI Rewriting feature can refine lengthy, disorganized speech into more polished and properly formatted text, utilizing either Cloud Cleanup or an on-device rewrite model when supported, thus enhancing the overall user experience. This dual functionality positions Paraspeech as a versatile tool for anyone seeking to streamline their writing process through voice.
Description
Windows Speech Recognition (WSR) performs effectively in applications that are compatible with it, such as MS Word, Outlook, and PowerPoint, allowing for seamless dictation where text is inserted directly into documents and commands like "Delete hedgehog" target specific text. However, in applications that are not optimized for WSR, including MS Excel, Gmail, and various programming environments, dictation struggles, as the spoken words do not integrate into the document text, and commands lack the capability to refer to existing document content. Vocola addresses these limitations by enabling direct dictation in WSR-unfriendly applications and facilitating the correction and alteration of the most recently spoken phrase. Both Vocola and WSR utilize the same speech profile, meaning that any enhancements from training, corrections, or adjustments to the speech dictionary will improve dictation capabilities in both systems equally. Unfortunately, on the Vista operating system, dictation in non-friendly applications is particularly problematic, as every spoken command triggers the correction panel, rendering the feature nearly ineffective. Overall, while WSR is beneficial for compatible applications, the experience can be significantly hindered when trying to use it in others.
API Access
Has API
API Access
Has API
Integrations
Gmail
Apple Notes
Microsoft Excel
Microsoft Outlook
Microsoft PowerPoint
Microsoft Word
Safari
Slack
Terminal
Integrations
Gmail
Apple Notes
Microsoft Excel
Microsoft Outlook
Microsoft PowerPoint
Microsoft Word
Safari
Slack
Terminal
Pricing Details
$14.99 per month
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Paraspeech
Country
United States
Website
paraspeech.com
Vendor Details
Company Name
Vocola 3
Founded
2002
Website
vocola.net/v3/Dictation.asp
Product Features
Product 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